@inproceedings{Winikoff2025ScoresheetXAI,
	address = {Detroit, MI, USA},
	title = {A {Scoresheet} for {Explainable} {AI}},
	url = {https://plibin.github.io/aamas-25-proceedings/pdfs/p2171.pdf},
	doi = {https://doi.org/10.48550/arXiv.2502.09861},
	abstract = {Explainability is important for the transparency of autonomous and intelligent systems and for helping to support the development of appropriate levels of trust. There has been considerable work on developing approaches for explaining systems and there are standards that specify requirements for transparency. However, there is a gap: the standards are too high-level and do not adequately specify requirements for explainability. This paper develops a scoresheet that can be used to specify explainability requirements or to assess the explainability aspects provided for particular applications. The scoresheet is developed by considering the requirements of a range of stakeholders and is applicable to Multiagent Systems as well as other AI technologies. We also provide guidance for how to use the scoresheet and illustrate its generality and usefulness by applying it to a range of applications.},
	booktitle = {24th {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems} ({AAMAS25})},
	author = {Winikoff, Michael and Thangarajah, John and Rodriguez, Sebastian},
	month = may,
	year = {2025},
}

Explainability is important for the transparency of autonomous and intelligent systems and for helping to support the development of appropriate levels of trust. There has been considerable work on developing approaches for explaining systems and there are standards that specify requirements for transparency. However, there is a gap: the standards are too high-level and do not adequately specify requirements for explainability. This paper develops a scoresheet that can be used to specify explainability requirements or to assess the explainability aspects provided for particular applications. The scoresheet is developed by considering the requirements of a range of stakeholders and is applicable to Multiagent Systems as well as other AI technologies. We also provide guidance for how to use the scoresheet and illustrate its generality and usefulness by applying it to a range of applications.

@inproceedings{Rodriguez2025MonitoringXAg,
	address = {Detroit, MI, USA},
	title = {Requirements-based {Explainability} for {Multi} {Agent} {Systems} ({Extended} {Abstract})},
	url = {https://plibin.github.io/aamas-25-proceedings/pdfs/p2726.pdf},
	abstract = {Explainability is essential for building trust in intelligent and autonomous systems. However, existing techniques for explainability focus on the behaviour of the system, but do not go back to the system’s requirements. We provide fully traceable explanations that link back to requirements, expressed as User and System stories, by extending previous work on explainable agents (XAg) that uses an agent design pattern. Our implementation leverages industry-grade mainstream monitoring tools.},
	booktitle = {24th {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems} ({AAMAS25})},
	author = {Rodriguez, Sebastian and Thangarajah, John and Winikoff, Michael},
	month = may,
	year = {2025},
}

Explainability is essential for building trust in intelligent and autonomous systems. However, existing techniques for explainability focus on the behaviour of the system, but do not go back to the system’s requirements. We provide fully traceable explanations that link back to requirements, expressed as User and System stories, by extending previous work on explainable agents (XAg) that uses an agent design pattern. Our implementation leverages industry-grade mainstream monitoring tools.

@inproceedings{Rodriguez2024Triqpan,
	address = {Auckland, New Zeland},
	series = {{AAMAS} '24},
	title = {Design {Patterns} for {Explainable} {Agents} ({XAg})},
	url = {https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p1621.pdf},
	abstract = {The ability to explain the behaviour of the AI systems is a key aspect
of building trust, especially for autonomous agent systems - how
does one trust an agent whose behaviour can not be explained? In
this work, we advocate the use of design patterns for developing
explainable-by-design agents (XAg), to ensure explainability is an
integral feature of agent systems rather than an “add-on” feature.
We present TriQPAN (Trigger, Query, Process, Action and Notify), a
design pattern for XAg. TriQPAN can be used to explain behaviours
of any agent architecture and we show how this can be done to
explain decisions such as why the agent chose to pursue a particular
goal, why or why didn’t the agent choose a particular plan to
achieve a goal, and so on. We term these queries as direct queries.
Our framework also supports temporal correlation queries such as
asking a search and rescue drone, “which locations did you visit
and why? ”. We implemented TriQPAN in the SARL agent language,
built-in to the goal reasoning engine, affording developers XAg
with minimal overhead. The implementation will be made available
for public use. We describe that implementation and apply it to two
case studies illustrating the explanations produced, in practice.},
	booktitle = {Proceedings of the 2024 {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems}},
	author = {Rodriguez, Sebastian and Thangarajah, John and Davey, Andrew},
	year = {2024},
	pages = {1621--1629},
}

The ability to explain the behaviour of the AI systems is a key aspect of building trust, especially for autonomous agent systems - how does one trust an agent whose behaviour can not be explained? In this work, we advocate the use of design patterns for developing explainable-by-design agents (XAg), to ensure explainability is an integral feature of agent systems rather than an “add-on” feature. We present TriQPAN (Trigger, Query, Process, Action and Notify), a design pattern for XAg. TriQPAN can be used to explain behaviours of any agent architecture and we show how this can be done to explain decisions such as why the agent chose to pursue a particular goal, why or why didn’t the agent choose a particular plan to achieve a goal, and so on. We term these queries as direct queries. Our framework also supports temporal correlation queries such as asking a search and rescue drone, “which locations did you visit and why? ”. We implemented TriQPAN in the SARL agent language, built-in to the goal reasoning engine, affording developers XAg with minimal overhead. The implementation will be made available for public use. We describe that implementation and apply it to two case studies illustrating the explanations produced, in practice.

@inproceedings{Rodriguez2023BDD,
	address = {Richland, SC},
	series = {{AAMAS} '23},
	title = {A {Behaviour}-{Driven} {Approach} for {Testing} {Requirements} via {User} and {System} {Stories} in {Agent} {Systems}},
	isbn = {978-1-4503-9432-1},
	url = {https://www.southampton.ac.uk/~eg/AAMAS2023/pdfs/p1182.pdf},
	doi = {10.5555/3545946.3598761},
	abstract = {Testing is a critical part of the software development cycle. This is even more important for autonomous systems, which can be challenging to test. In mainstream software engineering, Behaviour-Driven Development (BDD) is an Agile software development practice that is well accepted and widely used. It involves defining test cases for the expected system behaviour prior to developing the associated functionality. In this work, we present a BDD approach to testing the behavioural requirements of an agent system specified via User and System Stories (USS). USS is also based on established Agile processes and is shown to be intuitive and readily mapped to agent concepts. More specifically we extend USS so that they can be used for testing, and develop a behaviour-driven testing framework based on USS. We show how test cases can be developed, and how to evaluate the test cases by using a state-of-the-art mutation testing system, PITest, which we have integrated into our test framework. A key feature of our work is that we leverage a range of state-of-the-art development tools, inheriting the rich set of features they provide.},
	urldate = {2023-10-16},
	booktitle = {Proceedings of the 2023 {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems}},
	publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
	author = {Rodriguez, Sebastian and Thangarajah, John and Winikoff, Michael},
	month = may,
	year = {2023},
	keywords = {AOSE, behaviour-driven development, requirements testing, system stories, test-driven development testing, user stories},
	pages = {1182--1190},
}

Testing is a critical part of the software development cycle. This is even more important for autonomous systems, which can be challenging to test. In mainstream software engineering, Behaviour-Driven Development (BDD) is an Agile software development practice that is well accepted and widely used. It involves defining test cases for the expected system behaviour prior to developing the associated functionality. In this work, we present a BDD approach to testing the behavioural requirements of an agent system specified via User and System Stories (USS). USS is also based on established Agile processes and is shown to be intuitive and readily mapped to agent concepts. More specifically we extend USS so that they can be used for testing, and develop a behaviour-driven testing framework based on USS. We show how test cases can be developed, and how to evaluate the test cases by using a state-of-the-art mutation testing system, PITest, which we have integrated into our test framework. A key feature of our work is that we leverage a range of state-of-the-art development tools, inheriting the rich set of features they provide.

@inproceedings{Rodriguez2022TestingUSS,
	address = {Richland, SC},
	series = {{AAMAS} '22},
	title = {Testing {Requirements} via {User} and {System} {Stories} in {Agent} {Systems}},
	isbn = {978-1-4503-9213-6},
	url = {https://ifaamas.org/Proceedings/aamas2022/pdfs/p1119.pdf},
	abstract = {Agile software development is a popular and widely adopted practice due to its flexible and iterative nature that facilitates rapid prototyping. Recent work presented an agile approach to capturing requirements in agent systems via user and system stories. User and system stories present the requirements from the user and system perspective, respectively. Each story contains a set of acceptance criteria, which are a set of statements that identify the conditions under which the system behaviour can be accepted by the users or stakeholders. In this paper, we present a novel approach to testing the requirements that are specified via User and System stories in an agent system. We do this by developing a systematic approach to validating the execution traces output by the system against the specified acceptance criteria for each story. The approach identifies acceptance criteria that are met successfully in execution and those that fail. We present a fault model that categorizes the failures providing insight to the developers to address the failed cases. We classify three kinds of faults for a given acceptance criterion: (a) the trigger condition is never met; (b) when the trigger occurs the preconditions are not met; or (c) the trigger and preconditions are met but the resulting actions are not as expected. The motivating application of our work, which is also the test-bed for evaluation, is an agent-based simulation application for modelling the behaviours of civilians in a bushfire emergency scenario that is used in practice. We show our approach is able to successfully test and uncover requirements that were not met in this application.},
	urldate = {2022-05-12},
	booktitle = {Proceedings of the 21st {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems}},
	publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
	author = {Rodriguez, Sebastian and Thangarajah, John and Winikoff, Michael and Singh, Dhirendra},
	month = may,
	year = {2022},
	keywords = {AOSE, agile methodologies, engineering mas, requirements, testing},
	pages = {1119--1127},
}

Agile software development is a popular and widely adopted practice due to its flexible and iterative nature that facilitates rapid prototyping. Recent work presented an agile approach to capturing requirements in agent systems via user and system stories. User and system stories present the requirements from the user and system perspective, respectively. Each story contains a set of acceptance criteria, which are a set of statements that identify the conditions under which the system behaviour can be accepted by the users or stakeholders. In this paper, we present a novel approach to testing the requirements that are specified via User and System stories in an agent system. We do this by developing a systematic approach to validating the execution traces output by the system against the specified acceptance criteria for each story. The approach identifies acceptance criteria that are met successfully in execution and those that fail. We present a fault model that categorizes the failures providing insight to the developers to address the failed cases. We classify three kinds of faults for a given acceptance criterion: (a) the trigger condition is never met; (b) when the trigger occurs the preconditions are not met; or (c) the trigger and preconditions are met but the resulting actions are not as expected. The motivating application of our work, which is also the test-bed for evaluation, is an agent-based simulation application for modelling the behaviours of civilians in a bushfire emergency scenario that is used in practice. We show our approach is able to successfully test and uncover requirements that were not met in this application.

@inproceedings{Rodriguez2021USS,
	address = {Richland, SC},
	series = {{AAMAS} '21},
	title = {User and {System} {Stories}: {An} {Agile} {Approach} for {Managing} {Requirements} in {AOSE}},
	isbn = {978-1-4503-8307-3},
	shorttitle = {User and {System} {Stories}},
	url = {http://www.ifaamas.org/Proceedings/aamas2021/pdfs/p1064.pdf},
	doi = {10.5555/3461017.3461136},
	abstract = {The agile software development life cycle is widely used in industry today due to its highly flexible and iterative processes that facilitate rapid prototyping. There has been recent work in bringing concepts and processes from agile methodologies to agent-oriented software engineering (AOSE). We contribute to this effort by presenting in this paper a novel approach to capturing requirements of agent systems in AOSE using and extending agile concepts. In this paper, we propose to adopt and extend the well-known concept of User Stories to facilitate the development of agent systems. We introduce a novel concept, System Story, that defines requirements from the perspective of the system. These System Stories are refinements of User Stories and provide more intuitive mappings to agent concepts in the design and implementation. We show how our approach allows better traceability of requirements between stories and the different software development artifacts. We validate our proposal with a feature-based comparison to recent related work, and a preliminary user evaluation based on a drone simulation of a simple search and rescue case study.},
	urldate = {2021-04-19},
	booktitle = {Proceedings of the 20th {International} {Conference} on {Autonomous} {Agents} and {MultiAgent} {Systems}},
	publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
	author = {Rodriguez, Sebastian and Thangarajah, John and Winikoff, Michael},
	month = may,
	year = {2021},
	note = {keywords = \{engineering MAS, AOSE, agile methodologies\},
Presentation URL: https://underline.io/lecture/15417-user-and-system-stories-an-agile-approach-for-managing-requirements-in-aose},
	keywords = {AOSE, agile methodologies, engineering MAS},
	pages = {1064--1072},
}

The agile software development life cycle is widely used in industry today due to its highly flexible and iterative processes that facilitate rapid prototyping. There has been recent work in bringing concepts and processes from agile methodologies to agent-oriented software engineering (AOSE). We contribute to this effort by presenting in this paper a novel approach to capturing requirements of agent systems in AOSE using and extending agile concepts. In this paper, we propose to adopt and extend the well-known concept of User Stories to facilitate the development of agent systems. We introduce a novel concept, System Story, that defines requirements from the perspective of the system. These System Stories are refinements of User Stories and provide more intuitive mappings to agent concepts in the design and implementation. We show how our approach allows better traceability of requirements between stories and the different software development artifacts. We validate our proposal with a feature-based comparison to recent related work, and a preliminary user evaluation based on a drone simulation of a simple search and rescue case study.

@article{Araujo2018Aire,
	title = {A metamodeling approach for the identification of organizational smells in multi-agent systems: application to {ASPECS}},
	volume = {49},
	copyright = {All rights reserved},
	issn = {0269-2821},
	url = {http://www.sebastianrodriguez.com.ar/files/Araujo_et_al_2018_A_metamodeling_approach_for_the_identification_of_organizational_smells_in.pdf},
	doi = {10.1007/s10462-016-9521-7},
	abstract = {Software Quality is one of the most important subjects in the Process Development Software, especially in large and complex systems. Much effort has been devoted to the development of techniques and concepts to improve software quality over the years. We are especially interested on smells, which represent anomalies or flaws in the design/code that can have serious consequences in maintenance or future development of the systems. These techniques have a strong development in the Object Oriented paradigm, however, very few studies were conducted in the agent oriented paradigm. In this paper we focus on the detection of design smells applied to multiagent systems models based on the organizational approach, named Organizational Design Smells (ODS). Early and automatic detection of these ODS allows reducing the costs and development times, while increasing the final product’s quality. To achieve this objective, validation rules were defined based in the EVL language. The approach is illustrated with two examples, their validation rules, and the refactoring solutions proposed.},
	language = {English},
	number = {2},
	journal = {Artificial Intelligence Review},
	author = {Araujo, Pedro and Rodriguez, Sebastian and Hilaire, Vincent},
	month = feb,
	year = {2018},
	note = {First Online: 20 October 2016,
JCR2016 : 2.627,
H-Index: 58,
Scimago 2017: Q1},
	keywords = {Agent Oriented Software Engineering (AOSE), Design smells, Organization approach, RA:AOSE, RA:MAS, Validation rules, conicetInforme1617},
	pages = {183--210},
}

Software Quality is one of the most important subjects in the Process Development Software, especially in large and complex systems. Much effort has been devoted to the development of techniques and concepts to improve software quality over the years. We are especially interested on smells, which represent anomalies or flaws in the design/code that can have serious consequences in maintenance or future development of the systems. These techniques have a strong development in the Object Oriented paradigm, however, very few studies were conducted in the agent oriented paradigm. In this paper we focus on the detection of design smells applied to multiagent systems models based on the organizational approach, named Organizational Design Smells (ODS). Early and automatic detection of these ODS allows reducing the costs and development times, while increasing the final product’s quality. To achieve this objective, validation rules were defined based in the EVL language. The approach is illustrated with two examples, their validation rules, and the refactoring solutions proposed.

@inproceedings{Rodriguez2014Sarl,
	address = {Warsaw, Poland},
	title = {{SARL}: a general-purpose agent-oriented programming language},
	volume = {3},
	copyright = {All rights reserved},
	isbn = {978-1-4799-4142-1},
	url = {http://www.sebastianrodriguez.com.ar/files/Rodriguez_et_al_2014_SARL.pdf},
	doi = {10.1109/WI-IAT.2014.156},
	abstract = {Complex software systems development require appropriate high-level features to better and easily tackle the new requirements in terms of interactions, concurrency and distribution. This requires a paradigm change in software engineering and corresponding programming languages.
We are convinced that agent-oriented programming may be the support for this change by focusing on a small corpus of commonly accepted concepts and the corresponding programming language in line with the current developers' programming practices.
This papers introduces SARL, a new general-purpose agent-oriented programming language undertaking this challenge.
SARL comes with its full support in the Eclipse IDE for compilation and debugging, and a new version 2.0 of the Janus platform for execution purposes.
The main perspective that guided the creation of SARL is the establishment of an open and easily extensible language.
Our expectation is to provide the community with a common forum in terms of a first working testbed to study and compare various programming alternatives and associated metamodels.},
	publisher = {IEEE Computer Society Press},
	author = {Rodriguez, Sebastian and Gaud, Nicolas and Galland, Stéphane},
	year = {2014},
	keywords = {Agent Oriented Programming, Agent Programming Languages, Complex Systems, Context, Eclipse IDE, Holonic multiagent system, Janus platform, Java, Metamodels, Multiagent systems, Programming, Programming Language, Reactive power, Recursive agents, SARL, Software, Software Engineering, Software agents, complex software systems, developer programming practices},
	pages = {103--110},
}

Complex software systems development require appropriate high-level features to better and easily tackle the new requirements in terms of interactions, concurrency and distribution. This requires a paradigm change in software engineering and corresponding programming languages. We are convinced that agent-oriented programming may be the support for this change by focusing on a small corpus of commonly accepted concepts and the corresponding programming language in line with the current developers' programming practices. This papers introduces SARL, a new general-purpose agent-oriented programming language undertaking this challenge. SARL comes with its full support in the Eclipse IDE for compilation and debugging, and a new version 2.0 of the Janus platform for execution purposes. The main perspective that guided the creation of SARL is the establishment of an open and easily extensible language. Our expectation is to provide the community with a common forum in terms of a first working testbed to study and compare various programming alternatives and associated metamodels.

@inproceedings{Winikoff2025ScoresheetXAI,
	address = {Detroit, MI, USA},
	title = {A {Scoresheet} for {Explainable} {AI}},
	url = {https://plibin.github.io/aamas-25-proceedings/pdfs/p2171.pdf},
	doi = {https://doi.org/10.48550/arXiv.2502.09861},
	abstract = {Explainability is important for the transparency of autonomous and intelligent systems and for helping to support the development of appropriate levels of trust. There has been considerable work on developing approaches for explaining systems and there are standards that specify requirements for transparency. However, there is a gap: the standards are too high-level and do not adequately specify requirements for explainability. This paper develops a scoresheet that can be used to specify explainability requirements or to assess the explainability aspects provided for particular applications. The scoresheet is developed by considering the requirements of a range of stakeholders and is applicable to Multiagent Systems as well as other AI technologies. We also provide guidance for how to use the scoresheet and illustrate its generality and usefulness by applying it to a range of applications.},
	booktitle = {24th {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems} ({AAMAS25})},
	author = {Winikoff, Michael and Thangarajah, John and Rodriguez, Sebastian},
	month = may,
	year = {2025},
}

Explainability is important for the transparency of autonomous and intelligent systems and for helping to support the development of appropriate levels of trust. There has been considerable work on developing approaches for explaining systems and there are standards that specify requirements for transparency. However, there is a gap: the standards are too high-level and do not adequately specify requirements for explainability. This paper develops a scoresheet that can be used to specify explainability requirements or to assess the explainability aspects provided for particular applications. The scoresheet is developed by considering the requirements of a range of stakeholders and is applicable to Multiagent Systems as well as other AI technologies. We also provide guidance for how to use the scoresheet and illustrate its generality and usefulness by applying it to a range of applications.

@inproceedings{Rodriguez2024Triqpan,
	address = {Auckland, New Zeland},
	series = {{AAMAS} '24},
	title = {Design {Patterns} for {Explainable} {Agents} ({XAg})},
	url = {https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p1621.pdf},
	abstract = {The ability to explain the behaviour of the AI systems is a key aspect
of building trust, especially for autonomous agent systems - how
does one trust an agent whose behaviour can not be explained? In
this work, we advocate the use of design patterns for developing
explainable-by-design agents (XAg), to ensure explainability is an
integral feature of agent systems rather than an “add-on” feature.
We present TriQPAN (Trigger, Query, Process, Action and Notify), a
design pattern for XAg. TriQPAN can be used to explain behaviours
of any agent architecture and we show how this can be done to
explain decisions such as why the agent chose to pursue a particular
goal, why or why didn’t the agent choose a particular plan to
achieve a goal, and so on. We term these queries as direct queries.
Our framework also supports temporal correlation queries such as
asking a search and rescue drone, “which locations did you visit
and why? ”. We implemented TriQPAN in the SARL agent language,
built-in to the goal reasoning engine, affording developers XAg
with minimal overhead. The implementation will be made available
for public use. We describe that implementation and apply it to two
case studies illustrating the explanations produced, in practice.},
	booktitle = {Proceedings of the 2024 {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems}},
	author = {Rodriguez, Sebastian and Thangarajah, John and Davey, Andrew},
	year = {2024},
	pages = {1621--1629},
}

The ability to explain the behaviour of the AI systems is a key aspect of building trust, especially for autonomous agent systems - how does one trust an agent whose behaviour can not be explained? In this work, we advocate the use of design patterns for developing explainable-by-design agents (XAg), to ensure explainability is an integral feature of agent systems rather than an “add-on” feature. We present TriQPAN (Trigger, Query, Process, Action and Notify), a design pattern for XAg. TriQPAN can be used to explain behaviours of any agent architecture and we show how this can be done to explain decisions such as why the agent chose to pursue a particular goal, why or why didn’t the agent choose a particular plan to achieve a goal, and so on. We term these queries as direct queries. Our framework also supports temporal correlation queries such as asking a search and rescue drone, “which locations did you visit and why? ”. We implemented TriQPAN in the SARL agent language, built-in to the goal reasoning engine, affording developers XAg with minimal overhead. The implementation will be made available for public use. We describe that implementation and apply it to two case studies illustrating the explanations produced, in practice.

@inproceedings{Rodriguez2024XAgBlueSky,
	address = {Auckland, New Zeland},
	series = {{AAMAS} '24},
	title = {Explainable {Agents} ({XAg}) by {Design}},
	url = {https://www.ifaamas.org/Proceedings/aamas2024/pdfs/p2712.pdf},
	abstract = {The likes of ChatGPT has propelled the use of AI techniques beyond
our community’s expectations. Along with this, the fear of AI has
also risen, in particular around the ability, or lack thereof, of the AI
system to explain its behaviours. Explainability is a key element of
building trust and an important issue for our community. In this
paper we advocate for agents that are explainable-by-design, that is,
explainability is built into the development of agents rather than an
afterthought. We propose key features of an explainable agent (XAg)
system and propose a general framework that enables explainability.
We advocate the use of design patterns to develop XAgs and propose
a general design pattern that can be used for any agent architecture.
We instantiate our framework for goal-based agents and implement
the framework for the SARL agent programming language coupled
with a state-of-the-art event management system. We make a call to
the developers of other agent programming languages (APLs) in our
community to follow suit by instantiating the general framework
we propose into their APL, perhaps even enhancing the framework
we present. We also propose an open repository of design patterns
and examples for agent systems. If nothing else, we hope this paper
will inspire further work on XAg from the design perspective as it
is critical that multi agent systems are explainable by design!},
	booktitle = {Proceedings of the 2024 {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems} ({Blue} {Sky})},
	author = {Rodriguez, Sebastian and Thangarajah, John},
	year = {2024},
	pages = {2712--2716},
}

The likes of ChatGPT has propelled the use of AI techniques beyond our community’s expectations. Along with this, the fear of AI has also risen, in particular around the ability, or lack thereof, of the AI system to explain its behaviours. Explainability is a key element of building trust and an important issue for our community. In this paper we advocate for agents that are explainable-by-design, that is, explainability is built into the development of agents rather than an afterthought. We propose key features of an explainable agent (XAg) system and propose a general framework that enables explainability. We advocate the use of design patterns to develop XAgs and propose a general design pattern that can be used for any agent architecture. We instantiate our framework for goal-based agents and implement the framework for the SARL agent programming language coupled with a state-of-the-art event management system. We make a call to the developers of other agent programming languages (APLs) in our community to follow suit by instantiating the general framework we propose into their APL, perhaps even enhancing the framework we present. We also propose an open repository of design patterns and examples for agent systems. If nothing else, we hope this paper will inspire further work on XAg from the design perspective as it is critical that multi agent systems are explainable by design!

@article{Rodriguez2023Swarms,
	title = {A {Methodological} {Approach} for the analysis and design of {Human}-{Swarm} interactions based upon {Feedback} {Loops}},
	volume = {217},
	issn = {0957-4174},
	url = {https://www.sciencedirect.com/science/article/pii/S0957417422025015},
	doi = {10.1016/j.eswa.2022.119482},
	abstract = {A new era of humans interacting seamlessly with devices has began. Systems composed of humans and devices are being deployed over a wide range of domains such as smart grids, smart cities, industry 4.0, among others. In many cases, the algorithms proposed to achieve the intelligent decision-making are based on decentralized and collective behaviours including swarm intelligence. Although clear benefits can be attributed to these approaches, the analysis and design of such systems is a difficult task. Furthermore, enabling humans (e.g. operators) to guide and influence the swarms is still an open research question. In this paper we propose a methodological approach to enable swarms to be influenced by humans with minimal intervention or modification (if any) to the original underlying principles. This approach allows to translate high level goals, as conceptualized by human operators, into influencing factors to the swarm algorithms; and thus allowing humans to guide and interpret the resolution process. To illustrate and evaluate this proposal, we apply the methodology to a swarm of drones using Particle Swarm Optimization (PSO) algorithm for search and rescue operations. Experimentations show that, by using the resulting system, humans are able to influence the PSO algorithm overall results using high level abstractions. Even more, the PSO algorithm mechanics are not modified and influences are derived solely by following the proposed steps. Finally, we discuss the limitations of the approach and application to other swarm intelligence algorithms.},
	journal = {Expert Systems With Applications},
	author = {Rodriguez, Sebastian and Hilaire, Vincent},
	year = {2023},
	note = {keywords = \{Software engineering of artificial intelligence, Agent-oriented software engineering, Human–swarm interaction, Human–machine teams, Multiagent systems, Feedback loops\}
share\_url = \{https://authors.elsevier.com/a/1gSVJ3PiGTLt4t\}},
	pages = {119482},
}

A new era of humans interacting seamlessly with devices has began. Systems composed of humans and devices are being deployed over a wide range of domains such as smart grids, smart cities, industry 4.0, among others. In many cases, the algorithms proposed to achieve the intelligent decision-making are based on decentralized and collective behaviours including swarm intelligence. Although clear benefits can be attributed to these approaches, the analysis and design of such systems is a difficult task. Furthermore, enabling humans (e.g. operators) to guide and influence the swarms is still an open research question. In this paper we propose a methodological approach to enable swarms to be influenced by humans with minimal intervention or modification (if any) to the original underlying principles. This approach allows to translate high level goals, as conceptualized by human operators, into influencing factors to the swarm algorithms; and thus allowing humans to guide and interpret the resolution process. To illustrate and evaluate this proposal, we apply the methodology to a swarm of drones using Particle Swarm Optimization (PSO) algorithm for search and rescue operations. Experimentations show that, by using the resulting system, humans are able to influence the PSO algorithm overall results using high level abstractions. Even more, the PSO algorithm mechanics are not modified and influences are derived solely by following the proposed steps. Finally, we discuss the limitations of the approach and application to other swarm intelligence algorithms.

@article{vukovic_performance_2021,
	title = {Performance degrades less under increased workload with the addition of speech control in a dynamic environment},
	volume = {96},
	issn = {0003-6870},
	url = {https://www.sciencedirect.com/science/article/pii/S0003687021001332},
	doi = {10.1016/j.apergo.2021.103486},
	abstract = {This research empirically evaluates the introduction of speech to existing keyboard and mouse input modalities in an application used to control aircraft in a simulated, complex and dynamic environment. Task performance and task performance degradation are assessed for three levels of workload. Previous studies have evaluated task performance using these modalities however, only a couple have evaluated task performance under varying workload. Even though speech is a common addition to modern control interfaces, the effect of varying workload on this combination of control modalities has not yet been reported. Thirty-six participants commanded simulated aircraft through generated obstacle courses to reach a Combat Air Patrol (CAP) point while also responding to a secondary task. There were nine conditions that varied the control modality (Keyboard and Mouse (KM), Voice (V), and Keyboard, Mouse and Voice (KMV)), and workload by varying the number of aircraft being controlled (low, medium and high). Results showed that KM outperformed KMV and V for the low and medium workload levels. However, task performance with KMV was found to degrade the least as workload increased. KMV and KM were found to enable significantly more correct responses to the secondary task which was delivered aurally. Participants reported a preference for the combined modalities (KMV), self-assessing that KMV most reduced their workload. This research suggests that the addition of a speech interface to existing keyboard and mouse modalities, for control of aircraft in a simulation, may help manage cognitive load and may assist in controlling more aircraft under higher workloads.},
	language = {en},
	urldate = {2021-06-14},
	journal = {Applied Ergonomics},
	author = {Vukovic, Maria and Cavedon, Lawrence and Thangarajah, John and Rodriguez, Sebastian},
	month = oct,
	year = {2021},
	keywords = {Control modality, Keyboard, Mouse, Simulated aircraft control, Speech input, Varied workload conditions},
	pages = {103486},
}

This research empirically evaluates the introduction of speech to existing keyboard and mouse input modalities in an application used to control aircraft in a simulated, complex and dynamic environment. Task performance and task performance degradation are assessed for three levels of workload. Previous studies have evaluated task performance using these modalities however, only a couple have evaluated task performance under varying workload. Even though speech is a common addition to modern control interfaces, the effect of varying workload on this combination of control modalities has not yet been reported. Thirty-six participants commanded simulated aircraft through generated obstacle courses to reach a Combat Air Patrol (CAP) point while also responding to a secondary task. There were nine conditions that varied the control modality (Keyboard and Mouse (KM), Voice (V), and Keyboard, Mouse and Voice (KMV)), and workload by varying the number of aircraft being controlled (low, medium and high). Results showed that KM outperformed KMV and V for the low and medium workload levels. However, task performance with KMV was found to degrade the least as workload increased. KMV and KM were found to enable significantly more correct responses to the secondary task which was delivered aurally. Participants reported a preference for the combined modalities (KMV), self-assessing that KMV most reduced their workload. This research suggests that the addition of a speech interface to existing keyboard and mouse modalities, for control of aircraft in a simulation, may help manage cognitive load and may assist in controlling more aircraft under higher workloads.

@misc{Rodriguez2020_Talk_Human_Interaction_ICRA,
	address = {Virtual},
	type = {Keynote},
	title = {Modelling and {Implementation} of {Recursive} {Agents}},
	url = {https://hsiworkshopicra2020.wixsite.com/hsiworkshopicra2020},
	language = {English},
	author = {Rodriguez, Sebastian},
	month = may,
	year = {2020},
	keywords = {Holonic Systems, Human Agent, Human Agent Teaming (HAT), SARL, SARL agent-programming language, Talk},
}

@article{kim_special_2018,
	title = {Special issue on smart interactions in cyber-physical systems: {Humans}, agents, robots, machines, and sensors},
	volume = {40},
	issn = {2233-7326},
	shorttitle = {Special issue on smart interactions in cyber-physical systems},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.4218/etrij.18.3018.0000},
	doi = {10.4218/etrij.18.3018.0000},
	abstract = {In recent years, there has been increasing interaction between humans and non‐human systems as we move further beyond the industrial age, the information age, and as we move into the fourth‐generation society. The ability to distinguish between human and non‐human capabilities has become more difficult to discern. Given this, it is common that cyber‐physical systems (CPSs) are rapidly integrated with human functionality, and humans have become increasingly dependent on CPSs to perform their daily routines.
The constant indicators of a future where human and non‐human CPSs relationships consistently interact and where they allow each other to navigate through a set of non‐trivial goals is an interesting and rich area of research, discovery, and practical work area. The evidence of con- vergence has rapidly gained clarity, demonstrating that we can use complex combinations of sensors, artificial intelli- gence, and data to augment human life and knowledge. To expand the knowledge in this area, we should explain how to model, design, validate, implement, and experiment with these complex systems of interaction, communication, and networking, which will be developed and explored in this special issue. This special issue will include ideas of the future that are relevant for understanding, discerning, and developing the relationship between humans and non‐ human CPSs as well as the practical nature of systems that facilitate the integration between humans, agents, robots, machines, and sensors (HARMS).},
	language = {en},
	number = {4},
	urldate = {2018-08-16},
	journal = {ETRI Journal},
	author = {Kim, Donghan and Rodriguez, Sebastian and Matson, Eric T. and Kim, Gerard Jounghyun},
	month = aug,
	year = {2018},
	pages = {417--420},
}

In recent years, there has been increasing interaction between humans and non‐human systems as we move further beyond the industrial age, the information age, and as we move into the fourth‐generation society. The ability to distinguish between human and non‐human capabilities has become more difficult to discern. Given this, it is common that cyber‐physical systems (CPSs) are rapidly integrated with human functionality, and humans have become increasingly dependent on CPSs to perform their daily routines. The constant indicators of a future where human and non‐human CPSs relationships consistently interact and where they allow each other to navigate through a set of non‐trivial goals is an interesting and rich area of research, discovery, and practical work area. The evidence of con- vergence has rapidly gained clarity, demonstrating that we can use complex combinations of sensors, artificial intelli- gence, and data to augment human life and knowledge. To expand the knowledge in this area, we should explain how to model, design, validate, implement, and experiment with these complex systems of interaction, communication, and networking, which will be developed and explored in this special issue. This special issue will include ideas of the future that are relevant for understanding, discerning, and developing the relationship between humans and non‐ human CPSs as well as the practical nature of systems that facilitate the integration between humans, agents, robots, machines, and sensors (HARMS).

@inproceedings{moradi_framework_2025,
	address = {Hawaii, USA},
	title = {A {Framework} for {Constructing} {Agent}-based {Models} for {Evaluating} {Emergency} {Evacuation} {Procedures}; {A} {Case} {Study} applied to {Egaleo}, {Greece}},
	abstract = {Planning and preparing for evacuations
of populations during emergencies requires a
multifaceted approach covering the essential concerns
of understanding hazard risk, preparing critical
infrastructure for egress and shelter, determining
the makeup of the population at risk, understanding
how that population will respond in the event of
an emergency, and developing robust evacuation
procedures and policies. While tools and methods
often exist for understanding these concerns separately,
these do not allow decision-makers to systematically
understand their inter-connections and the implication
of change in one dimension on the other.
To address this challenge, we introduce a
comprehensive framework tailored to support
emergency management decision makers in the
evaluation of community evacuation plans and
procedures. Central to our approach is the use of
micro-simulations that model known human behaviours
in emergencies for evacuating populations. Our
framework encompasses the five dimensions of
Infrastructure, Population Demographics, Evacuation
Policy, Hazard Model, and Human Behavior Model, and
allow users to systematically build ”what-if” scenarios
that introduce changes in different dimensions to test
the robustness of evacuation policies.
We present a case study of employing this framework
in Egaleo, Greece, a seismic-prone region, as part
of the European HORIZON project C2IMPRESS, in
collaboration with local government. We showcase
the effectiveness and relevance of our approach
in enhancing emergency response strategies within
dynamic and high-stakes environments.},
	booktitle = {58th {Hawaii} {International} {Conference} on {System} {Sciences} ({HICSS})},
	author = {Moradi, Hossein and Iskandar, Rouba and Rodriguez, Sebastian and Dugdale, Julie and Singh, Dhirendra and Tzempelikos, Dimitrios and Sfetsos, Athanasios},
	month = jul,
	year = {2025},
}

Planning and preparing for evacuations of populations during emergencies requires a multifaceted approach covering the essential concerns of understanding hazard risk, preparing critical infrastructure for egress and shelter, determining the makeup of the population at risk, understanding how that population will respond in the event of an emergency, and developing robust evacuation procedures and policies. While tools and methods often exist for understanding these concerns separately, these do not allow decision-makers to systematically understand their inter-connections and the implication of change in one dimension on the other. To address this challenge, we introduce a comprehensive framework tailored to support emergency management decision makers in the evaluation of community evacuation plans and procedures. Central to our approach is the use of micro-simulations that model known human behaviours in emergencies for evacuating populations. Our framework encompasses the five dimensions of Infrastructure, Population Demographics, Evacuation Policy, Hazard Model, and Human Behavior Model, and allow users to systematically build ”what-if” scenarios that introduce changes in different dimensions to test the robustness of evacuation policies. We present a case study of employing this framework in Egaleo, Greece, a seismic-prone region, as part of the European HORIZON project C2IMPRESS, in collaboration with local government. We showcase the effectiveness and relevance of our approach in enhancing emergency response strategies within dynamic and high-stakes environments.

@inproceedings{Rodriguez2022TestingUSS,
	address = {Richland, SC},
	series = {{AAMAS} '22},
	title = {Testing {Requirements} via {User} and {System} {Stories} in {Agent} {Systems}},
	isbn = {978-1-4503-9213-6},
	url = {https://ifaamas.org/Proceedings/aamas2022/pdfs/p1119.pdf},
	abstract = {Agile software development is a popular and widely adopted practice due to its flexible and iterative nature that facilitates rapid prototyping. Recent work presented an agile approach to capturing requirements in agent systems via user and system stories. User and system stories present the requirements from the user and system perspective, respectively. Each story contains a set of acceptance criteria, which are a set of statements that identify the conditions under which the system behaviour can be accepted by the users or stakeholders. In this paper, we present a novel approach to testing the requirements that are specified via User and System stories in an agent system. We do this by developing a systematic approach to validating the execution traces output by the system against the specified acceptance criteria for each story. The approach identifies acceptance criteria that are met successfully in execution and those that fail. We present a fault model that categorizes the failures providing insight to the developers to address the failed cases. We classify three kinds of faults for a given acceptance criterion: (a) the trigger condition is never met; (b) when the trigger occurs the preconditions are not met; or (c) the trigger and preconditions are met but the resulting actions are not as expected. The motivating application of our work, which is also the test-bed for evaluation, is an agent-based simulation application for modelling the behaviours of civilians in a bushfire emergency scenario that is used in practice. We show our approach is able to successfully test and uncover requirements that were not met in this application.},
	urldate = {2022-05-12},
	booktitle = {Proceedings of the 21st {International} {Conference} on {Autonomous} {Agents} and {Multiagent} {Systems}},
	publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
	author = {Rodriguez, Sebastian and Thangarajah, John and Winikoff, Michael and Singh, Dhirendra},
	month = may,
	year = {2022},
	keywords = {AOSE, agile methodologies, engineering mas, requirements, testing},
	pages = {1119--1127},
}

Agile software development is a popular and widely adopted practice due to its flexible and iterative nature that facilitates rapid prototyping. Recent work presented an agile approach to capturing requirements in agent systems via user and system stories. User and system stories present the requirements from the user and system perspective, respectively. Each story contains a set of acceptance criteria, which are a set of statements that identify the conditions under which the system behaviour can be accepted by the users or stakeholders. In this paper, we present a novel approach to testing the requirements that are specified via User and System stories in an agent system. We do this by developing a systematic approach to validating the execution traces output by the system against the specified acceptance criteria for each story. The approach identifies acceptance criteria that are met successfully in execution and those that fail. We present a fault model that categorizes the failures providing insight to the developers to address the failed cases. We classify three kinds of faults for a given acceptance criterion: (a) the trigger condition is never met; (b) when the trigger occurs the preconditions are not met; or (c) the trigger and preconditions are met but the resulting actions are not as expected. The motivating application of our work, which is also the test-bed for evaluation, is an agent-based simulation application for modelling the behaviours of civilians in a bushfire emergency scenario that is used in practice. We show our approach is able to successfully test and uncover requirements that were not met in this application.

@inproceedings{bordini_multidimensional_2015,
	address = {Istanbul, Turkey},
	title = {A multidimensional environment implementation for enhancing agent interaction},
	copyright = {All rights reserved},
	isbn = {978-1-4503-3413-6},
	url = {http://www.sebastianrodriguez.com.ar/files/Galland_et_al_2015_A_multidimensional_environment_implementation_for_enhancing_agent_interaction.pdf},
	abstract = {The environment, as a space shared between agents, is a key component of multiagent systems (MAS). Depending on systems, this space may integrate physical, communication or social dimensions. Each of them has its own process and rules to support agents' interaction. For instance, in the physical dimension, the rules may be based on the agents' location. The agents' interaction is then contextualized and the environment allows a multiagent control since it performs the interactions according to the state and rules of the MAS. The dimensions of the environment are generally connected either in an application dependent adhoc way outside of the agents or within each agent. In order to ensure a multiagent control, the relations between dimensions must be explicit outside of the agents. Using these relations between the environment dimensions, the interaction becomes also multi-dimensional. In this paper we propose to formalize rules and mechanisms to make this connection outside of the agents and in a generic way.},
	language = {english},
	booktitle = {14th {Int}. {Conf}. on {Autonomous} {Agents} and {Multiagent} {Systems} ({AAMAS15})},
	publisher = {ACM In-Cooperation},
	author = {Galland, Stéphane and Balbo, Flavien and Gaud, Nicolas and Rodriguez, Sebastian and Picard, Gauthier and Boissier, Olivier},
	editor = {Bordini, Rafael and Elkind, Edith},
	month = may,
	year = {2015},
	keywords = {Agent Based Simulation, Complex Systems, SARL, Simulation techniques, tools and environments},
	pages = {1801--1802},
}

The environment, as a space shared between agents, is a key component of multiagent systems (MAS). Depending on systems, this space may integrate physical, communication or social dimensions. Each of them has its own process and rules to support agents' interaction. For instance, in the physical dimension, the rules may be based on the agents' location. The agents' interaction is then contextualized and the environment allows a multiagent control since it performs the interactions according to the state and rules of the MAS. The dimensions of the environment are generally connected either in an application dependent adhoc way outside of the agents or within each agent. In order to ensure a multiagent control, the relations between dimensions must be explicit outside of the agents. Using these relations between the environment dimensions, the interaction becomes also multi-dimensional. In this paper we propose to formalize rules and mechanisms to make this connection outside of the agents and in a generic way.

@incollection{rodriguez_holonic_2007,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {A {Holonic} {Approach} to {Model} and {Deploy} {Large} {Scale} {Simulations}},
	copyright = {2007 Springer-Verlag Berlin Heidelberg},
	isbn = {978-3-540-76536-3 978-3-540-76539-4},
	url = {http://www.sebastianrodriguez.com.ar/files/Rodriguez_et_al_2007_A_Holonic_Approach_to_Model_and_Deploy_Large_Scale_Simulations.pdf},
	abstract = {Multi-Agent Based Simulations (MABS) for real-world problems may require a large number of agents. A possible solution is to distribute the simulation in multiple machines. Thus, we are forced to consider how Large Scale MABS can be deployed in order to have an efficient system. Even more, we need to consider how to cluster those agents in the different execution servers. In this paper we propose an approach based on a holonic model for the construction and update of clusters of agents. We also present two modules to facilitate the deployment and control of distributed simulations.},
	number = {4442},
	urldate = {2013-11-21},
	booktitle = {Multi-{Agent}-{Based} {Simulation} {VII}},
	publisher = {Springer Berlin Heidelberg},
	author = {Rodriguez, Sebastian and Hilaire, Vincent and Koukam, Abder},
	editor = {Antunes, Luis and Takadama, Keiki},
	month = jan,
	year = {2007},
	note = {tex.doi= 10.1007/978-3-540-76539-4\_9
tex.url\_other= http://link.springer.com/chapter/10.1007/978-3-540-76539-4\_9},
	keywords = {Artificial Intelligence (incl. Robotics), Computer Appl. in Social and Behavioral Sciences, Computer Communication Networks, Information Systems Applications (incl.Internet), Simulation and Modeling},
	pages = {112--127},
}

Multi-Agent Based Simulations (MABS) for real-world problems may require a large number of agents. A possible solution is to distribute the simulation in multiple machines. Thus, we are forced to consider how Large Scale MABS can be deployed in order to have an efficient system. Even more, we need to consider how to cluster those agents in the different execution servers. In this paper we propose an approach based on a holonic model for the construction and update of clusters of agents. We also present two modules to facilitate the deployment and control of distributed simulations.

@incollection{rodriguez_holonic_2006,
	series = {Lecture {Notes} in {Computer} {Science}},
	title = {Holonic {Modeling} of {Environments} for {Situated} {Multi}-agent {Systems}},
	copyright = {©2006 Springer Berlin Heidelberg},
	isbn = {978-3-540-32614-4 978-3-540-32615-1},
	url = {http://www.sebastianrodriguez.com.ar/files/Rodriguez_et_al_2006_Holonic_Modeling_of_Environments_for_Situated_Multi-agent_Systems.pdf},
	abstract = {In a Multi-Agent Based Simulation (MABS) special attention must go to the analysis, modeling and implementation of the environment. Environments for simulation of real world problems may be complex. Seeing the environment as a monolithic structure only reduces our capacity to handle large scale, real-world environments. In order to support this type of environments, we propose the use of an holonic perspective to represent the environment and the agents. In our approach, agents and environment are represented by holons. The environment defines a holarchy. Each agent belong to a specific holon in this holarchy following its needs.},
	number = {3830},
	urldate = {2013-11-21},
	booktitle = {Environments for {Multi}-{Agent} {Systems} {II}},
	publisher = {Springer Berlin Heidelberg},
	author = {Rodriguez, Sebastian and Hilaire, Vincent and Koukam, Abder},
	editor = {Weyns, Danny and Parunak, H. Van Dyke and Michel, Fabien},
	month = jan,
	year = {2006},
	note = {tex.url\_other= http://link.springer.com/chapter/10.1007/11678809\_2},
	keywords = {Artificial Intelligence (incl. Robotics), Computer Communication Networks, Simulation, environment of MAS},
	pages = {18--31},
}

In a Multi-Agent Based Simulation (MABS) special attention must go to the analysis, modeling and implementation of the environment. Environments for simulation of real world problems may be complex. Seeing the environment as a monolithic structure only reduces our capacity to handle large scale, real-world environments. In order to support this type of environments, we propose the use of an holonic perspective to represent the environment and the agents. In our approach, agents and environment are represented by holons. The environment defines a holarchy. Each agent belong to a specific holon in this holarchy following its needs.

@article{jimenez_phase_2020,
	title = {Phase identification and substation detection using data analysis on limited electricity consumption measurements},
	volume = {187},
	issn = {03787796},
	url = {https://linkinghub.elsevier.com/retrieve/pii/S0378779620302546},
	doi = {10.1016/j.epsr.2020.106450},
	language = {en},
	urldate = {2020-06-17},
	journal = {Electric Power Systems Research},
	author = {Jimenez, Victor Adrian and Will, Adrian and Rodriguez, Sebastian},
	month = oct,
	year = {2020},
	pages = {106450},
}

@article{lizondo_artificial_2018,
	title = {An {Artificial} {Immune} {Network} for {Distributed} {Demand}-{Side} {Management} in {Smart} {Grids}},
	volume = {438},
	issn = {0020-0255},
	url = {http://www.sebastianrodriguez.com.ar/files/Lizondo_et_al_2018_An_Artificial_Immune_Network_for_Distributed_Demand-Side_Management_in_Smart.pdf},
	doi = {10.1016/j.ins.2018.01.039},
	abstract = {In this work we present a Distributed Demand-Side Management system based on the Artificial Immune Network algorithm. It implements an intelligent, distributed and autonomous control of the customer’s Air Conditioning devices in order to meet the desired demand. The system is particularly adapted to tackle the Peak Load problem that appears in Tropical and Subtropical climates due to the use of thousands of these devices at the same time. The design follows the guidelines set by the Smart Grid paradigm, in the sense that it is fault tolerant, distributed and self-controlled. It requires minimal communication infrastructure when compared to a centralized system.
The algorithm was evaluated using synthetic and real data. We define Maximal and Average Tolerance as performance metrics, and show that the system keeps the consumption within 1\% of the given load limit in all 5 cases.},
	urldate = {2018-02-09},
	journal = {Information Sciences},
	author = {Lizondo, Diego and Rodriguez, Sebastian and Will, Adrián and Jimenez, Victor and Gotay, Jorge},
	month = apr,
	year = {2018},
	note = {tex.note= JCR2016 : 4.832, Scimago 2017 : Q1, H-Index : 142},
	keywords = {Artificial Immune Network, Demand-Side Management, Distributed systems, Peak load, RA:MAS, Smart Grid, conicetInforme1617},
	pages = {32--45},
}

In this work we present a Distributed Demand-Side Management system based on the Artificial Immune Network algorithm. It implements an intelligent, distributed and autonomous control of the customer’s Air Conditioning devices in order to meet the desired demand. The system is particularly adapted to tackle the Peak Load problem that appears in Tropical and Subtropical climates due to the use of thousands of these devices at the same time. The design follows the guidelines set by the Smart Grid paradigm, in the sense that it is fault tolerant, distributed and self-controlled. It requires minimal communication infrastructure when compared to a centralized system. The algorithm was evaluated using synthetic and real data. We define Maximal and Average Tolerance as performance metrics, and show that the system keeps the consumption within 1% of the given load limit in all 5 cases.

@patent{Lizondo2016Patente,
	address = {Buenos Aires},
	title = {Disposición de unidades electrónicas y procedimiento para controlar y regular el consumo de energía de aparatos en una red eléctrica.},
	abstract = {La presente invención se refiere a una disposición de unidades electrónicas y procedimiento para controlar y regular el consumo de energía de aparatos en una red eléctrica, para evitar cortes de suministro de energía eléctrica por picos de consumo, y para proteger las instalaciones de proveedores y usuarios, de manera autónoma, descentralizada, y maximizando el Confort Térmico Humano, la cual ha sido elaborada por el Grupo de Investigación en Tecnologías Informáticas Avanzadas (GITIA) de la Facultad Regional Tucumán de la Universidad Tecnológica Nacional y por el Consejo Nacional de Investigaciones Científicas y Técnicas.},
	nationality = {Argentina},
	language = {Spanish},
	assignee = {UTN (85{\textbackslash}\%) - CONICET (15{\textbackslash}\%)},
	number = {16221767 PATENTES},
	author = {Lizondo, Diego and Rodriguez, Sebastian and Will, Adrian and Jimenez, Victor},
	year = {2016},
	note = {English: Arrangement of electronic units and procedure to control and regulate the energy consumption of devices in an electrical network},
	keywords = {conicetInforme1617},
}

La presente invención se refiere a una disposición de unidades electrónicas y procedimiento para controlar y regular el consumo de energía de aparatos en una red eléctrica, para evitar cortes de suministro de energía eléctrica por picos de consumo, y para proteger las instalaciones de proveedores y usuarios, de manera autónoma, descentralizada, y maximizando el Confort Térmico Humano, la cual ha sido elaborada por el Grupo de Investigación en Tecnologías Informáticas Avanzadas (GITIA) de la Facultad Regional Tucumán de la Universidad Tecnológica Nacional y por el Consejo Nacional de Investigaciones Científicas y Técnicas.

@incollection{Descamps2016,
	address = {Cham},
	title = {An {Experience} of {Engineering} of {MAS} for {Smart} {Environments}: {Extension} of {ASPECS}},
	isbn = {978-3-319-39345-2},
	url = {http://www.sebastianrodriguez.com.ar/files/Descamps_et_al_2016_An_Experience_of_Engineering_of_MAS_for_Smart_Environments.pdf},
	abstract = {This paper presents a methodological approach for the engi- neering of Smart Environments based upon Multi- Agent Systems. This approach is an extension of an existing MAS methodology, namely AS- PECS. The extension of ASPECS is allowed by the Situational Method Engineering principles underlying ASPECS and takes the form of several existing modified activities and corresponding meta-model elements. The key elements that are targeted by the contribution are: the identification of goals hierarchy, the expression of detailed requirements and associa- tions of goals to sensors/effectors, different levels of ontologies to describe on the one hand, the problem conceptualization, and, on the other hand, the several involved expertness. The remaining, existing activities, refine the models in order to identify organizational structures/behaviours and theirs agentification. The approach is illustrated through a case study that consists in a platform dedicated to the Monitoring of patients with heart failures.},
	booktitle = {Intelligent {Interactive} {Multimedia} {Systems} and {Services} 2016},
	publisher = {Springer International Publishing},
	author = {Descamps, Philippe and Hilaire, Vincent and Lamotte, Olivier and Rodriguez, Sebastian},
	editor = {Pietro, Giuseppe De and Gallo, Luigi and Howlett, Robert J. and Jain, Lakhmi C.},
	year = {2016},
	note = {tex.doi= 10.1007/978-3-319-39345-2\_58
tex.url\_other= http://dx.doi.org/10.1007/978-3-319-39345-2\_58},
	keywords = {conicetInforme1617},
	pages = {649--658},
}

This paper presents a methodological approach for the engi- neering of Smart Environments based upon Multi- Agent Systems. This approach is an extension of an existing MAS methodology, namely AS- PECS. The extension of ASPECS is allowed by the Situational Method Engineering principles underlying ASPECS and takes the form of several existing modified activities and corresponding meta-model elements. The key elements that are targeted by the contribution are: the identification of goals hierarchy, the expression of detailed requirements and associa- tions of goals to sensors/effectors, different levels of ontologies to describe on the one hand, the problem conceptualization, and, on the other hand, the several involved expertness. The remaining, existing activities, refine the models in order to identify organizational structures/behaviours and theirs agentification. The approach is illustrated through a case study that consists in a platform dedicated to the Monitoring of patients with heart failures.