Computational and Mathematical Organization Theory, Oct 1, 2006
We extend the logical model of agency known as the KGP model, to support agents with normative co... more We extend the logical model of agency known as the KGP model, to support agents with normative concepts, based on the roles an agent plays and the obligations and prohibitions that result from playing these roles. The proposed framework illustrates how the resulting normative concepts, including the roles, can evolve dynamically during the lifetime of the agent. Furthermore, we illustrate how these concepts can be combined with the existing capabilities of KGP agents in order to plan for their goals, react to changes in the environment, and interact with other agents. Our approach gives an executable specification of normative concepts that can be used directly for prototyping applications.
2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Nov 1, 2021
We propose a novel knowledge representation framework called COGNISIM that supports game theoreti... more We propose a novel knowledge representation framework called COGNISIM that supports game theoretic simulation experiments using cognitive agents. The framework allows an experimenter to evolve a population of such agents with strategies expressed teleo-reactively as logic programs. When agents encounter each other, events take place in the environment, caused either by agent actions or by environment processes. Such events change the environment's internal state, and these changes are then observed by agents that, in turn, decide to take new actions that affect the environment. This loop continues until the terminating conditions of the simulation are met. Using this framework, we show how to repeat experiments from the literature based on Axelrod's tournament. We also evaluate our platform's performance in efficiently supporting large simulations in game theoretic settings.
ABSTRACT Very commonly, multi-agent systems built for ubiquitous computing and ambient intelligen... more ABSTRACT Very commonly, multi-agent systems built for ubiquitous computing and ambient intelligence applications require from their members to perform collaborative tasks or to attempt to communicate regarding potentially unknown objects in their environment. The specific class of this type of systems that constitutes the domain for the proposed research defines multi-agent systems utilizing agents that encompass high-level symbolic name worlds that are linked to their environment via low level sensory input. A successful outcome when attempting collaborative tasks in such systems is always dependent on the ability of the agents to refer to the correct objects in their communication. In my research I will pursue an approach towards confronting the above problem and propose a solution. This solution will be applied in this category of multi-agent systems enabling them to deal with the imperative to verify that all agents refer to the correct object in order for the outcome of a collaborative task upon it or the communication regarding it to be successful.
Un système multi-agent adaptatif pour la réallocation de tâches au sein d'un job MapReduce Volume... more Un système multi-agent adaptatif pour la réallocation de tâches au sein d'un job MapReduce Volume 3, n o 5-6 (2022), p. 557-585.
Change your habit to hang or waste the time to only chat with your friends. It is done by your ev... more Change your habit to hang or waste the time to only chat with your friends. It is done by your everyday, don't you feel bored? Now, we will show you the new habit that, actually it's a very old habit to do that can make your life more qualified. When feeling bored of always chatting with your friends all free time, you can find the book enPDF logic programs norms and action essays in honor of marek j sergot on the occasion of his 60th birthday lecture notes in computer science and then read it.
Automated Bug Detection (ABD) in video games is composed of two distinct but complementary proble... more Automated Bug Detection (ABD) in video games is composed of two distinct but complementary problems: automated game exploration and bug identification. Automated game exploration has received much recent attention, spurred on by developments in fields such as reinforcement learning. The complementary problem of identifying the bugs present in a player's experience has for the most part relied on the manual specification of rules. Although it is widely recognised that many bugs of interest cannot be identified with such methods, little progress has been made in this direction. In this work we show that it is possible to identify a range of perceptual bugs using learning-based methods by making use of only the rendered game screen as seen by the player. To support our work, we have developed World of Bugs (WOB), an open platform for testing ABD methods in 3D game environments.
The AISB'05 Convention Social Intelligence and Interaction in Animals, Robots and Agents Above al... more The AISB'05 Convention Social Intelligence and Interaction in Animals, Robots and Agents Above all, the human animal is social. For an artificially intelligent system, how could it be otherwise? We stated in our Call for Participation "The AISB'05 convention with the theme Social Intelligence and Interaction in Animals, Robots and Agents aims to facilitate the synthesis of new ideas, encourage new insights as well as novel applications, mediate new collaborations, and provide a context for lively and stimulating discussions in this exciting, truly interdisciplinary, and quickly growing research area that touches upon many deep issues regarding the nature of intelligence in human and other animals, and its potential application to robots and other artefacts". Why is the theme of Social Intelligence and Interaction interesting to an Artificial Intelligence and Robotics community? We know that intelligence in humans and other animals has many facets and is expressed in a variety of ways in how the individual in its lifetime-or a population on an evolutionary timescale-deals with, adapts to, and co-evolves with the environment. Traditionally, social or emotional intelligence have been considered different from a more problem-solving, often called "rational", oriented view of human intelligence. However, more and more evidence from a variety of different research fields highlights the important role of social, emotional intelligence and interaction across all facets of intelligence in humans. The Convention theme Social Intelligence and Interaction in Animals, Robots and Agents reflects a current trend towards increasingly interdisciplinary approaches that are pushing the boundaries of traditional science and are necessary in order to answer deep questions regarding the social nature of intelligence in humans and other animals, as well as to address the challenge of synthesizing computational agents or robotic artifacts that show aspects of biological social intelligence. Exciting new developments are emerging from collaborations among computer scientists, roboticists, psychologists, sociologists, cognitive scientists, primatologists, ethologists and researchers from other disciplines, e.g. leading to increasingly sophisticated simulation models of socially intelligent agents, or to a new generation of robots that are able to learn from and socially interact with each other or with people. Such interdisciplinary work advances our understanding of social intelligence in nature, and leads to new theories, models, architectures and designs in the domain of Artificial Intelligence and other sciences of the artificial. New advancements in computer and robotic technology facilitate the emergence of multi-modal "natural" interfaces between computers or robots and people, including embodied conversational agents or robotic pets/assistants/companions that we are increasingly sharing our home and work space with. People tend to create certain relationships with such socially intelligent artifacts, and are even willing to accept them as helpers in healthcare, therapy or rehabilitation. Thus, socially intelligent artifacts are becoming part of our lives, including many desirable as well as possibly undesirable effects, and Artificial Intelligence and Cognitive Science research can play an important role in addressing many of the huge scientific challenges involved. Keeping an open mind towards other disciplines, embracing work from a variety of disciplines studying humans as well as non-human animals, might help us to create artifacts that might not only do their job, but that do their job right. Thus, the convention hopes to provide a home for state-of-the-art research as well as a discussion forum for innovative ideas and approaches, pushing the frontiers of what is possible and/or desirable in this exciting, growing area. The feedback to the initial Call for Symposia Proposals was overwhelming. Ten symposia were accepted (ranging from one-day to three-day events), organized by UK, European as well as international experts in the field of Social Intelligence and Interaction.
International Joint Conference on Artificial Intelligence, Aug 3, 2013
We propose a method for learning causal relations within high-dimensional tensor data as they are... more We propose a method for learning causal relations within high-dimensional tensor data as they are typically recorded in non-experimental databases. The method allows the simultaneous inclusion of numerous dimensions within the data analysis such as samples, time and domain variables construed as tensors. In such tensor data we exploit and integrate non-Gaussian models and tensor analytic algorithms in a novel way. We prove that we can determine simple causal relations independently of how complex the dimensionality of the data is. We rely on a statistical decomposition that flattens higher-dimensional data tensors into matrices. This decomposition preserves the causal information and is therefore suitable for structure learning of causal graphical models, where a causal relation can be generalised beyond dimension, for example, over all time points. Related methods either focus on a set of samples for instantaneous effects or look at one sample for effects at certain time points. We evaluate the resulting algorithm and discuss its performance both with synthetic and real-world data.
The coordination of distributed processing is of great interest to a number of research communiti... more The coordination of distributed processing is of great interest to a number of research communities. However these research communities, such as those involved in e-science GRIDs and multi-agent systems, view this problem from disparate viewpoints. This paper aims to contribute to the necessary reconciliation of these perspectives. By demonstrating the coordination of processes whether reactive (such as web services) or proactive (such as autonomous agents) can be done with a single representation using a protocol language, RASA. The multi-agent paradigm introduces, into any model of distributed systems, flexibility and autonomy that can be daunting and intimidating to scientists accustomed to more orthodox approaches. It is for this reason that it is important that the model for coordination of this system is reliable, verifiable, inspectable, referable, composable and executable. The language RASA provides this functionality, which we extend its use for not only agent interaction protocols but also to express workflows. The language for expression then becomes the domain of discourse as well as potentially the language for the workflow's execution.
We present a formal model for agent-oriented Virtual Organisations (VOs) for service grids and we... more We present a formal model for agent-oriented Virtual Organisations (VOs) for service grids and we study an associated operational model for the creation of VOs. The model is intended to be used for describing different service grid applications based on multiple agents and, as a result, it abstracts away from any realisation choices of service grid applications, the agents involved to support the applications and their interactions. Within the proposed framework VOs are created within societies of agents, where agents are abstractly characterised by goals and roles they can play within VOs. In turn, VOs are abstractly characterised by the agents participating in them with specific roles, as well as the workflow of services and corresponding contracts suitable for achieving the goals of the participating agents. We illustrate the proposed framework with an earth observation scenario, we discuss implementation issues, and we compare our approach with existing work.
We investigate the application of abductive logic programming, an existing framework for knowledg... more We investigate the application of abductive logic programming, an existing framework for knowledge representation and reasoning, for specifying the knowledge and behaviour of software agents that need to access resources in a global computing environment. The framework allows agents that need resources to join artificial societies where those resources are available. We show how to endow agents with the capability of becoming and ceasing to be members of societies, for different categories of artificial agent societies, and ...
A human user is centrally involved in a Decision Support System (DSS) task, whereas for an autono... more A human user is centrally involved in a Decision Support System (DSS) task, whereas for an autonomous agent system, a user's role is a more abstract notion of oversight and approval. In this paper, we examine the potential integration of a multi-agent architecture into a DSS. The motivation in this work is to utilise autonomous agent problemsolvers within a suitable multi-agent framework in such a way as to realise and generalise the capabilities of a DSS, while maintaining the DSS characteristic of significant user involvement. The approach taken is to employ agents both as domain problem solvers as well as to manage the interaction with the user as part of the semi-autonomous design. We consider the construction of an agent-based DSS based upon the KGP model of agency and detail how the design of a DSS may benefit from agent technology in general and KGP agents in particular (and vice versa). A framework for agent-enhanced DSS is presented which is more general than those presented previously. We show how the architectural framework used for KGP agents can be specialised to realise enhanced DSS capabilities. RÉSUMÉ. L'ensemble des.
We investigate the application of a logical model of agency, known as the KGP model, to develop a... more We investigate the application of a logical model of agency, known as the KGP model, to develop agents for ambient intelligence applications. Using a concrete scenario, we illustrate how the logical formalism employed by a KGP agent allows a person to access the surrounding ambient through the agent in a transparent manner. We evaluate our claims by implementing the resulting interactions in PROSOCS, a prototype multi-agent systems platform that allows KGP agents to be deployed as components of ambient intelligence applications.
HAL (Le Centre pour la Communication Scientifique Directe), Jul 3, 2019
Nous étudions une stratégie qui tient compte de la localité des ressources pour équilibrer les ch... more Nous étudions une stratégie qui tient compte de la localité des ressources pour équilibrer les charges dans un système distribué. Cette stratégie permet aux agents coopératifs d'identifier une allocation non équilibrée, voire de déclencher des enchères concurrentes pour réallouer localement certaines des tâches. Les tâches sont réallouées en tenant compte de l'accessibilité des ressources pour les agents ; elles sont exécutées conformément aux capacités des noeuds de calcul sur lesquels se trouvent les agents. Ce processus de négociation dynamique et continu est concurrent à l'exécution des tâches, ce qui permet d'adapter l'allocation des tâches aux perturbations (exécution de tâche, chute de performance d'un noeud). Nous évaluons cette stratégie dans le cadre du déploiement multi-agents de MapReduce. Ce patron de conception permet le traitement distribué de données massives. Les résultats empiriques démontrent que notre stratégie améliore significativement le temps d'exécution du traitement d'un jeu de données.
MagnetDroid is a novel artificial intelligence framework that integrates a security ontology, a m... more MagnetDroid is a novel artificial intelligence framework that integrates a security ontology, a multi-agent organisation, and a logical reasoning procedure to help build a bridge between the worlds of Android application analysis and law, with respect to privacy. Our contribution helps identify violations of the law by Android applications, as well as predict legal consequences. The resulting implementation of MagnetDroid can be useful to privacy-concerned users in order to acknowledge problems with the privacy of the applications they use, to application developers/publishers to help them identify which problems to fix, and to lawyers in order to provide an additional level of interpretation for any court when considering the privacy of Android applications.
We study the development of a distributed, agent-based, simulation environment where autonomous a... more We study the development of a distributed, agent-based, simulation environment where autonomous agents execute e-commerce contracts. We present a multi-agent architecture in which contracts are represented as a set of commitments that an agent must be capable of monitoring and reason with in order to be able to verify that the contract is not violated during interaction. We employ the JADE agent platform to build the multi-agent simulation infrastructure, and the Reactive Event Calculus to provide agent reasoning for monitoring and verification of contracts. We then experimentally evaluate the performance of our system by analysing the time and memory requirements as the number of agents increases, and by looking whether the behaviours of agents have any significant effect on the system’s overall performance.
Computational and Mathematical Organization Theory, Oct 1, 2006
We extend the logical model of agency known as the KGP model, to support agents with normative co... more We extend the logical model of agency known as the KGP model, to support agents with normative concepts, based on the roles an agent plays and the obligations and prohibitions that result from playing these roles. The proposed framework illustrates how the resulting normative concepts, including the roles, can evolve dynamically during the lifetime of the agent. Furthermore, we illustrate how these concepts can be combined with the existing capabilities of KGP agents in order to plan for their goals, react to changes in the environment, and interact with other agents. Our approach gives an executable specification of normative concepts that can be used directly for prototyping applications.
2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI), Nov 1, 2021
We propose a novel knowledge representation framework called COGNISIM that supports game theoreti... more We propose a novel knowledge representation framework called COGNISIM that supports game theoretic simulation experiments using cognitive agents. The framework allows an experimenter to evolve a population of such agents with strategies expressed teleo-reactively as logic programs. When agents encounter each other, events take place in the environment, caused either by agent actions or by environment processes. Such events change the environment's internal state, and these changes are then observed by agents that, in turn, decide to take new actions that affect the environment. This loop continues until the terminating conditions of the simulation are met. Using this framework, we show how to repeat experiments from the literature based on Axelrod's tournament. We also evaluate our platform's performance in efficiently supporting large simulations in game theoretic settings.
ABSTRACT Very commonly, multi-agent systems built for ubiquitous computing and ambient intelligen... more ABSTRACT Very commonly, multi-agent systems built for ubiquitous computing and ambient intelligence applications require from their members to perform collaborative tasks or to attempt to communicate regarding potentially unknown objects in their environment. The specific class of this type of systems that constitutes the domain for the proposed research defines multi-agent systems utilizing agents that encompass high-level symbolic name worlds that are linked to their environment via low level sensory input. A successful outcome when attempting collaborative tasks in such systems is always dependent on the ability of the agents to refer to the correct objects in their communication. In my research I will pursue an approach towards confronting the above problem and propose a solution. This solution will be applied in this category of multi-agent systems enabling them to deal with the imperative to verify that all agents refer to the correct object in order for the outcome of a collaborative task upon it or the communication regarding it to be successful.
Un système multi-agent adaptatif pour la réallocation de tâches au sein d'un job MapReduce Volume... more Un système multi-agent adaptatif pour la réallocation de tâches au sein d'un job MapReduce Volume 3, n o 5-6 (2022), p. 557-585.
Change your habit to hang or waste the time to only chat with your friends. It is done by your ev... more Change your habit to hang or waste the time to only chat with your friends. It is done by your everyday, don't you feel bored? Now, we will show you the new habit that, actually it's a very old habit to do that can make your life more qualified. When feeling bored of always chatting with your friends all free time, you can find the book enPDF logic programs norms and action essays in honor of marek j sergot on the occasion of his 60th birthday lecture notes in computer science and then read it.
Automated Bug Detection (ABD) in video games is composed of two distinct but complementary proble... more Automated Bug Detection (ABD) in video games is composed of two distinct but complementary problems: automated game exploration and bug identification. Automated game exploration has received much recent attention, spurred on by developments in fields such as reinforcement learning. The complementary problem of identifying the bugs present in a player's experience has for the most part relied on the manual specification of rules. Although it is widely recognised that many bugs of interest cannot be identified with such methods, little progress has been made in this direction. In this work we show that it is possible to identify a range of perceptual bugs using learning-based methods by making use of only the rendered game screen as seen by the player. To support our work, we have developed World of Bugs (WOB), an open platform for testing ABD methods in 3D game environments.
The AISB'05 Convention Social Intelligence and Interaction in Animals, Robots and Agents Above al... more The AISB'05 Convention Social Intelligence and Interaction in Animals, Robots and Agents Above all, the human animal is social. For an artificially intelligent system, how could it be otherwise? We stated in our Call for Participation "The AISB'05 convention with the theme Social Intelligence and Interaction in Animals, Robots and Agents aims to facilitate the synthesis of new ideas, encourage new insights as well as novel applications, mediate new collaborations, and provide a context for lively and stimulating discussions in this exciting, truly interdisciplinary, and quickly growing research area that touches upon many deep issues regarding the nature of intelligence in human and other animals, and its potential application to robots and other artefacts". Why is the theme of Social Intelligence and Interaction interesting to an Artificial Intelligence and Robotics community? We know that intelligence in humans and other animals has many facets and is expressed in a variety of ways in how the individual in its lifetime-or a population on an evolutionary timescale-deals with, adapts to, and co-evolves with the environment. Traditionally, social or emotional intelligence have been considered different from a more problem-solving, often called "rational", oriented view of human intelligence. However, more and more evidence from a variety of different research fields highlights the important role of social, emotional intelligence and interaction across all facets of intelligence in humans. The Convention theme Social Intelligence and Interaction in Animals, Robots and Agents reflects a current trend towards increasingly interdisciplinary approaches that are pushing the boundaries of traditional science and are necessary in order to answer deep questions regarding the social nature of intelligence in humans and other animals, as well as to address the challenge of synthesizing computational agents or robotic artifacts that show aspects of biological social intelligence. Exciting new developments are emerging from collaborations among computer scientists, roboticists, psychologists, sociologists, cognitive scientists, primatologists, ethologists and researchers from other disciplines, e.g. leading to increasingly sophisticated simulation models of socially intelligent agents, or to a new generation of robots that are able to learn from and socially interact with each other or with people. Such interdisciplinary work advances our understanding of social intelligence in nature, and leads to new theories, models, architectures and designs in the domain of Artificial Intelligence and other sciences of the artificial. New advancements in computer and robotic technology facilitate the emergence of multi-modal "natural" interfaces between computers or robots and people, including embodied conversational agents or robotic pets/assistants/companions that we are increasingly sharing our home and work space with. People tend to create certain relationships with such socially intelligent artifacts, and are even willing to accept them as helpers in healthcare, therapy or rehabilitation. Thus, socially intelligent artifacts are becoming part of our lives, including many desirable as well as possibly undesirable effects, and Artificial Intelligence and Cognitive Science research can play an important role in addressing many of the huge scientific challenges involved. Keeping an open mind towards other disciplines, embracing work from a variety of disciplines studying humans as well as non-human animals, might help us to create artifacts that might not only do their job, but that do their job right. Thus, the convention hopes to provide a home for state-of-the-art research as well as a discussion forum for innovative ideas and approaches, pushing the frontiers of what is possible and/or desirable in this exciting, growing area. The feedback to the initial Call for Symposia Proposals was overwhelming. Ten symposia were accepted (ranging from one-day to three-day events), organized by UK, European as well as international experts in the field of Social Intelligence and Interaction.
International Joint Conference on Artificial Intelligence, Aug 3, 2013
We propose a method for learning causal relations within high-dimensional tensor data as they are... more We propose a method for learning causal relations within high-dimensional tensor data as they are typically recorded in non-experimental databases. The method allows the simultaneous inclusion of numerous dimensions within the data analysis such as samples, time and domain variables construed as tensors. In such tensor data we exploit and integrate non-Gaussian models and tensor analytic algorithms in a novel way. We prove that we can determine simple causal relations independently of how complex the dimensionality of the data is. We rely on a statistical decomposition that flattens higher-dimensional data tensors into matrices. This decomposition preserves the causal information and is therefore suitable for structure learning of causal graphical models, where a causal relation can be generalised beyond dimension, for example, over all time points. Related methods either focus on a set of samples for instantaneous effects or look at one sample for effects at certain time points. We evaluate the resulting algorithm and discuss its performance both with synthetic and real-world data.
The coordination of distributed processing is of great interest to a number of research communiti... more The coordination of distributed processing is of great interest to a number of research communities. However these research communities, such as those involved in e-science GRIDs and multi-agent systems, view this problem from disparate viewpoints. This paper aims to contribute to the necessary reconciliation of these perspectives. By demonstrating the coordination of processes whether reactive (such as web services) or proactive (such as autonomous agents) can be done with a single representation using a protocol language, RASA. The multi-agent paradigm introduces, into any model of distributed systems, flexibility and autonomy that can be daunting and intimidating to scientists accustomed to more orthodox approaches. It is for this reason that it is important that the model for coordination of this system is reliable, verifiable, inspectable, referable, composable and executable. The language RASA provides this functionality, which we extend its use for not only agent interaction protocols but also to express workflows. The language for expression then becomes the domain of discourse as well as potentially the language for the workflow's execution.
We present a formal model for agent-oriented Virtual Organisations (VOs) for service grids and we... more We present a formal model for agent-oriented Virtual Organisations (VOs) for service grids and we study an associated operational model for the creation of VOs. The model is intended to be used for describing different service grid applications based on multiple agents and, as a result, it abstracts away from any realisation choices of service grid applications, the agents involved to support the applications and their interactions. Within the proposed framework VOs are created within societies of agents, where agents are abstractly characterised by goals and roles they can play within VOs. In turn, VOs are abstractly characterised by the agents participating in them with specific roles, as well as the workflow of services and corresponding contracts suitable for achieving the goals of the participating agents. We illustrate the proposed framework with an earth observation scenario, we discuss implementation issues, and we compare our approach with existing work.
We investigate the application of abductive logic programming, an existing framework for knowledg... more We investigate the application of abductive logic programming, an existing framework for knowledge representation and reasoning, for specifying the knowledge and behaviour of software agents that need to access resources in a global computing environment. The framework allows agents that need resources to join artificial societies where those resources are available. We show how to endow agents with the capability of becoming and ceasing to be members of societies, for different categories of artificial agent societies, and ...
A human user is centrally involved in a Decision Support System (DSS) task, whereas for an autono... more A human user is centrally involved in a Decision Support System (DSS) task, whereas for an autonomous agent system, a user's role is a more abstract notion of oversight and approval. In this paper, we examine the potential integration of a multi-agent architecture into a DSS. The motivation in this work is to utilise autonomous agent problemsolvers within a suitable multi-agent framework in such a way as to realise and generalise the capabilities of a DSS, while maintaining the DSS characteristic of significant user involvement. The approach taken is to employ agents both as domain problem solvers as well as to manage the interaction with the user as part of the semi-autonomous design. We consider the construction of an agent-based DSS based upon the KGP model of agency and detail how the design of a DSS may benefit from agent technology in general and KGP agents in particular (and vice versa). A framework for agent-enhanced DSS is presented which is more general than those presented previously. We show how the architectural framework used for KGP agents can be specialised to realise enhanced DSS capabilities. RÉSUMÉ. L'ensemble des.
We investigate the application of a logical model of agency, known as the KGP model, to develop a... more We investigate the application of a logical model of agency, known as the KGP model, to develop agents for ambient intelligence applications. Using a concrete scenario, we illustrate how the logical formalism employed by a KGP agent allows a person to access the surrounding ambient through the agent in a transparent manner. We evaluate our claims by implementing the resulting interactions in PROSOCS, a prototype multi-agent systems platform that allows KGP agents to be deployed as components of ambient intelligence applications.
HAL (Le Centre pour la Communication Scientifique Directe), Jul 3, 2019
Nous étudions une stratégie qui tient compte de la localité des ressources pour équilibrer les ch... more Nous étudions une stratégie qui tient compte de la localité des ressources pour équilibrer les charges dans un système distribué. Cette stratégie permet aux agents coopératifs d'identifier une allocation non équilibrée, voire de déclencher des enchères concurrentes pour réallouer localement certaines des tâches. Les tâches sont réallouées en tenant compte de l'accessibilité des ressources pour les agents ; elles sont exécutées conformément aux capacités des noeuds de calcul sur lesquels se trouvent les agents. Ce processus de négociation dynamique et continu est concurrent à l'exécution des tâches, ce qui permet d'adapter l'allocation des tâches aux perturbations (exécution de tâche, chute de performance d'un noeud). Nous évaluons cette stratégie dans le cadre du déploiement multi-agents de MapReduce. Ce patron de conception permet le traitement distribué de données massives. Les résultats empiriques démontrent que notre stratégie améliore significativement le temps d'exécution du traitement d'un jeu de données.
MagnetDroid is a novel artificial intelligence framework that integrates a security ontology, a m... more MagnetDroid is a novel artificial intelligence framework that integrates a security ontology, a multi-agent organisation, and a logical reasoning procedure to help build a bridge between the worlds of Android application analysis and law, with respect to privacy. Our contribution helps identify violations of the law by Android applications, as well as predict legal consequences. The resulting implementation of MagnetDroid can be useful to privacy-concerned users in order to acknowledge problems with the privacy of the applications they use, to application developers/publishers to help them identify which problems to fix, and to lawyers in order to provide an additional level of interpretation for any court when considering the privacy of Android applications.
We study the development of a distributed, agent-based, simulation environment where autonomous a... more We study the development of a distributed, agent-based, simulation environment where autonomous agents execute e-commerce contracts. We present a multi-agent architecture in which contracts are represented as a set of commitments that an agent must be capable of monitoring and reason with in order to be able to verify that the contract is not violated during interaction. We employ the JADE agent platform to build the multi-agent simulation infrastructure, and the Reactive Event Calculus to provide agent reasoning for monitoring and verification of contracts. We then experimentally evaluate the performance of our system by analysing the time and memory requirements as the number of agents increases, and by looking whether the behaviours of agents have any significant effect on the system’s overall performance.
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Papers by Kostas Stathis