Multiagent Systems, Artificial Societies, and Simulated Organizations – serie

Extending Web Services Technologies addresses the rapidly growing impact of Multi-Agent Systems on web services tools and techniques. In particular, the book addresses the potential for MAS techniques to impact the difficult challenges that must be tackled for web services technology to realize its promises. The area of web services offers the multi-agent community exciting research possibilities, including similarities in system architectures, powerful tools, and a focus on issues such as trust and reliability. Likewise, techniques developed in the multi-agent research community promise to have a strong impact on this fast growing technology. The contents contain contributions by leading international researchers and professionals from both the web services and Multi-Agent Systems community. Topics include semantic web services and associated standards, architectures integrating agents and services, transactions, authorization, and service composition.

Knowledge, hidden in voluminous data repositories routinely created and maintained by today’s applications, can be extracted by data mining. The next step is to transform this discovered knowledge into the inference mechanisms or simply the behavior of agents and multi-agent systems. Agent Intelligence Through Data Mining addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. This book contains a methodology, tools and techniques, and several examples of agent-based applications developed with this approach. This volume focuses mainly on the use of data mining for smarter, more efficient agents.Agent Intelligence Through Data Mining is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Multi-Agent Programming is an essential reference for anyone interested in the most up-to-date developments in MAS programming. While previous research has focused on the development of formal and informal approaches to analyze and specify Multi-Agent Systems, this book focuses on the development of programming languages and tools which not only support MAS programming, but also implement key concepts of MAS in a unified framework.Part I describes approaches that rely on computational logic or process algebra – Jason, 3APL, IMPACT, and CLAIM/SyMPA. Part II presents languages and platforms that extend or are based on Java – JADE, Jadex and JACKTM. Part III provides two significant industry specific applications – The DEFACTO System for coordinating human-agent teams for disaster response, and the ARTIMIS rational dialogue agent technology. Also featured are seven appendices for quick reference and comparison.

Conflicts between agents acting in a multi-agent environment arise for different reasons, involve different concepts, and are dealt with in different ways, depending on the kind of agents and on the domain where they are considered. Agents may have conflicting beliefs, conflicting goals, or may have to share limited resources. Consequently, conflicts may be expressed as mere differences, or as contradictions, or even as social conflicts. They may be avoided, solved, kept, or even created deliberately. Conflicting Agents studies conflicts in the context of multi-agent systems, i.e. artificial societies modeled on the basis of autonomous, interacting agents. This book addresses questions about types of conflicts, conflict definitions and the use of conflicts as trigger functions for activities in multi-agent systems. The book is also dedicated to questions of conflict management, resolution and avoidance, i.e. the question of how agents cope with conflicts and conflicting situations.

Social Order in Multiagent Systems provides an overview of current approaches, problems, and considerations related to the study of norms and institutions in the context of multiagent systems. The contributions in this volume share the assumption that norms and other social institutions are of vital importance for the development of multiagent systems and agent-mediated interaction. Both formal and computational models of norms and normative systems are presented, including formal analysis of normative concepts and foundational models of norms; agent and systems architectures for implementing norms; and implemented systems. Social Order in Multiagent Systems is an excellent reference for researchers in artificial intelligence and computer science, and can be used as text for advanced level courses in multiagent systems.

Socially situated planning provides one mechanism for improving the social awareness ofagents. Obviously this work isin the preliminary stages and many of the limitation and the relationship to other work could not be addressed in such a short chapter. The chief limitation, of course, is the strong commitment to de?ning social reasoning solely atthe meta-level, which restricts the subtlety of social behavior. Nonetheless, our experience in some real-world military simulation applications suggest that the approach, even in its preliminary state, is adequate to model some social interactions, and certainly extends the sta- of-the art found in traditional training simulation systems. Acknowledgments This research was funded by the Army Research Institute under contract TAPC-ARI-BR References [1] J. Gratch. Emile: Marshalling passions in training and education. In Proceedings of the Fourth International Conference on Autonomous Agents, pages 325–332, New York, 2000. ACM Press. [2] J. Gratch and R. Hill. Continous planning and collaboration for command and control in joint synthetic battlespaces. In Proceedings of the 8th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1999. [3] B. Grosz and S. Kraus. Collaborative plans for complex group action. Arti?cial Intelli gence, 86(2):269–357, 1996. [4] A. Ortony, G. L. Clore, and A. Collins. The Cognitive Structure of Emotions. Cambridge University Press, 1988. [5] R.W.PewandA.S.Mavor,editors. Modeling Human and Organizational Behavior. National Academy Press, Washington D.C., 1998.

Conceptual Modelling of Multi-Agent Systems proposes the methodology and engineering environment CoMoMAS for the development of multi-agent systems. CoMoMAS is among the most elaborated and most often cited multi-agent development approaches available in the field. Its originality is to address the issue of the development of multi-agent systems (MAS) from a knowledge engineering perspective, which means that agents are seen as interacting entities having different kinds of knowledge, which is to be identified during development. Knowledge has played an important role for MAS development in the past, but CoMoMAS makes a step further in proposing a complete set of conceptual models and a solid methodology to guide the overall development process of a MAS-from design to validation.Conceptual Modelling of Multi-Agent Systems is an excellent reference for both researchers and practitioners in the broad area of distributed systems development. This book is of particular value from the point of view of computer science, including knowledge engineering, artificial intelligence, agent and multi-agent technology, and software engineering.

Game Theory And Decision Theory In Agent-Based Systems is a collection of papers from international leading researchers, that offers a broad view of the many ways game theory and decision theory can be applied in agent-based systems, from standard applications of the core elements of the theory to more cutting edge developments. The range of topics discussed in this book provide the reader with the first comprehensive volume that reflects both the depth and breadth of work in applying techniques from game theory and decision theory to design agent-based systems. Chapters include: Selecting Partners; Evolution of Agents with Moral Sentiments in an IPD Exercise; Dynamic Desires; Emotions and Personality; Decision-Theoretic Approach to Game Theory; Shopbot Economics; Finding the Best Way to Join in; Shopbots and Pricebots in Electronic Service Markets; Polynomial Time Mechanisms; Multi-Agent Q-learning and Regression Trees; Satisficing Equilibria; Investigating Commitment Flexibility in Multi-agent Contracts; Pricing in Agent Economies using Multi-agent Q-learning; Using Hypergames to Increase Planned Payoff and Reduce Risk; Bilateral Negotiation with Incomplete and Uncertain Information; Robust Combinatorial Auction Protocol against False-name Bids.

This text discusses the role of reputation in the achievement of social order. It proposes that reputation is an agent property that results from transmission of beliefs about how the agents are evaluated with regard to a socially desirable conduct. This desirable conduct represents one or another of the solutions to the problem of social order and may consist of co-operation or altruism, reciprocity, or norm obedience. The text distinguishes between image (direct evaluation of others) and reputation (propagating meta-belief, indirectly acquired) and investigates their effects with regard to both natural and electronic societies. The interplay between image and reputation, the processes leading to them and the set of decisions that agents make on their basis are demonstrated with supporting data from agent-based simulations.

Autonomy is a characterizing notion of agents, and intuitively it is rather unambiguous. The quality of autonomy is recognized when it is perceived or experienced, yet it is difficult to limit autonomy in a definition. The desire to build agents that exhibit a satisfactory quality of autonomy includes agents that have a long life, are highly independent, can harmonize their goals and actions with humans and other agents, and are generally socially adept. Agent Autonomy is a collection of papers from leading international researchers that approximate human intuition, dispel false attributions, and point the way to scholarly thinking about autonomy. A wide array of issues about sharing control and initiative between humans and machines, as well as issues about peer level agent interaction, are addressed.

Improvements in computer networking have heralded great expectations for computer-mediated distributed work. However, experience has revealed that, as information flow improves, a central problem for distributed workers is the administration, management and control of that information. Research into Computer Supported Cooperative Work (CSCW) investigates design methods and technologies for the support of collaboration, communication and coordination of distributed group work, both within and among organizations. In tandem with this focus on the support of distributed communication and collaboration, there have been exciting developments in the fields of Intelligent Agents and Distributed Artificial Intelligence (DAI), notably in the concepts, theories and deployment of intelligent agents as a means of distributing computer-based problem solving expertise. The paradigm of multi-agent systems forms a proposed basis for the design of CSCW architectures, the support of CSCW operations and for addressing some of the problems of cooperative working.The application of a multi-agent approach to CSCW makes information exchange among the participants easier by delivering support to the participants, assisting workflows and procedures, and providing convenient user interfaces to CSCW systems. Furthermore, the ideas inherent in such an approach are also applicable to other domains, such as support for interactive learning. Organizations that seek to exploit the advantages offered through CSCW will benefit from the integration of agents in the management and use of their corporate knowledge, especially with the advancement of wired or wireless networking, pervasive computing, and other information technologies. Agent Supported Cooperative Work describes the state of the art in this exciting new area, covering both theoretical foundations and practical applications of ASCW.

Distributed Sensor Networks is the first book of its kind to examine solutions to this problem using ideas taken from the field of multiagent systems. The field of multiagent systems has itself seen an exponential growth in the past decade, and has developed a variety of techniques for distributed resource allocation. Distributed Sensor Networks contains contributions from leading, international researchers describing a variety of approaches to this problem based on examples of implemented systems taken from a common distributed sensor network application; each approach is motivated, demonstrated and tested by way of a common challenge problem. The book focuses on both practical systems and their theoretical analysis, and is divided into three parts: the first part describes the common sensor network challenge problem; the second part explains the different technical approaches to the common challenge problem; and the third part provides results on the formal analysis of a number of approaches taken to address the challenge problem.

As information technologies become increasingly distributed and accessible to larger number of people and as commercial and government organizations are challenged to scale their applications and services to larger market shares, while reducing costs, there is demand for software methodologies and appli- tions to provide the following features: Richer application end-to-end functionality; Reduction of human involvement in the design and deployment of the software; Flexibility of software behaviour; and Reuse and composition of existing software applications and systems in novel or adaptive ways. When designing new distributed software systems, the above broad requi- ments and their translation into implementations are typically addressed by partial complementarities and overlapping technologies and this situation gives rise to significant software engineering challenges. Some of the challenges that may arise are: determining the components that the distributed applications should contain, organizing the application components, and determining the assumptions that one needs to make in order to implement distributed scalable and flexible applications, etc.

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc. Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

Knowledge, hidden in voluminous data repositories routinely created and maintained by today’s applications, can be extracted by data mining. The next step is to transform this discovered knowledge into the inference mechanisms or simply the behavior of agents and multi-agent systems. Agent Intelligence Through Data Mining addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. This book contains a methodology, tools and techniques, and several examples of agent-based applications developed with this approach. This volume focuses mainly on the use of data mining for smarter, more efficient agents.Agent Intelligence Through Data Mining is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.

Multi-Agent Programming is an essential reference for anyone interested in the most up-to-date developments in MAS programming. While previous research has focused on the development of formal and informal approaches to analyze and specify Multi-Agent Systems, this book focuses on the development of programming languages and tools which not only support MAS programming, but also implement key concepts of MAS in a unified framework.Part I describes approaches that rely on computational logic or process algebra – Jason, 3APL, IMPACT, and CLAIM/SyMPA. Part II presents languages and platforms that extend or are based on Java – JADE, Jadex and JACKTM. Part III provides two significant industry specific applications – The DEFACTO System for coordinating human-agent teams for disaster response, and the ARTIMIS rational dialogue agent technology. Also featured are seven appendices for quick reference and comparison.

As information technologies become increasingly distributed and accessible to larger number of people and as commercial and government organizations are challenged to scale their applications and services to larger market shares, while reducing costs, there is demand for software methodologies and appli- tions to provide the following features: Richer application end-to-end functionality; Reduction of human involvement in the design and deployment of the software; Flexibility of software behaviour; and Reuse and composition of existing software applications and systems in novel or adaptive ways. When designing new distributed software systems, the above broad requi- ments and their translation into implementations are typically addressed by partial complementarities and overlapping technologies and this situation gives rise to significant software engineering challenges. Some of the challenges that may arise are: determining the components that the distributed applications should contain, organizing the application components, and determining the assumptions that one needs to make in order to implement distributed scalable and flexible applications, etc.

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc. Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

Autonomy is a characterizing notion of agents, and intuitively it is rather unambiguous. The quality of autonomy is recognized when it is perceived or experienced, yet it is difficult to limit autonomy in a definition. The desire to build agents that exhibit a satisfactory quality of autonomy includes agents that have a long life, are highly independent, can harmonize their goals and actions with humans and other agents, and are generally socially adept. Agent Autonomy is a collection of papers from leading international researchers that approximate human intuition, dispel false attributions, and point the way to scholarly thinking about autonomy. A wide array of issues about sharing control and initiative between humans and machines, as well as issues about peer level agent interaction, are addressed.

Improvements in computer networking have heralded great expectations for computer-mediated distributed work. However, experience has revealed that, as information flow improves, a central problem for distributed workers is the administration, management and control of that information. Research into Computer Supported Cooperative Work (CSCW) investigates design methods and technologies for the support of collaboration, communication and coordination of distributed group work, both within and among organizations. In tandem with this focus on the support of distributed communication and collaboration, there have been exciting developments in the fields of Intelligent Agents and Distributed Artificial Intelligence (DAI), notably in the concepts, theories and deployment of intelligent agents as a means of distributing computer-based problem solving expertise. The paradigm of multi-agent systems forms a proposed basis for the design of CSCW architectures, the support of CSCW operations and for addressing some of the problems of cooperative working. The application of a multi-agent approach to CSCW makes information exchange among the participants easier by delivering support to the participants, assisting workflows and procedures, and providing convenient user interfaces to CSCW systems. Furthermore, the ideas inherent in such an approach are also applicable to other domains, such as support for interactive learning. Organizations that seek to exploit the advantages offered through CSCW will benefit from the integration of agents in the management and use of their corporate knowledge, especially with the advancement of wired or wireless networking, pervasive computing, and other information technologies. Agent Supported Cooperative Work describes the state of the art in this exciting new area, covering both theoretical foundations and practical applications of ASCW. It is the first book explicitly dedicated to ASCW, bringingtogether contributions from international experts in the field.

Distributed Sensor Networks is the first book of its kind to examine solutions to this problem using ideas taken from the field of multiagent systems. The field of multiagent systems has itself seen an exponential growth in the past decade, and has developed a variety of techniques for distributed resource allocation. Distributed Sensor Networks contains contributions from leading, international researchers describing a variety of approaches to this problem based on examples of implemented systems taken from a common distributed sensor network application; each approach is motivated, demonstrated and tested by way of a common challenge problem. The book focuses on both practical systems and their theoretical analysis, and is divided into three parts: the first part describes the common sensor network challenge problem; the second part explains the different technical approaches to the common challenge problem; and the third part provides results on the formal analysis of a number of approaches taken to address the challenge problem.

Conceptual Modelling of Multi-Agent Systems proposes the methodology and engineering environment CoMoMAS for the development of multi-agent systems. CoMoMAS is among the most elaborated and most often cited multi-agent development approaches available in the field. Its originality is to address the issue of the development of multi-agent systems (MAS) from a knowledge engineering perspective, which means that agents are seen as interacting entities having different kinds of knowledge, which is to be identified during development. Knowledge has played an important role for MAS development in the past, but CoMoMAS makes a step further in proposing a complete set of conceptual models and a solid methodology to guide the overall development process of a MAS-from design to validation.Conceptual Modelling of Multi-Agent Systems is an excellent reference for both researchers and practitioners in the broad area of distributed systems development. This book is of particular value from the point of view of computer science, including knowledge engineering, artificial intelligence, agent and multi-agent technology, and software engineering.

Game Theory And Decision Theory In Agent-Based Systems is a collection of papers from international leading researchers, that offers a broad view of the many ways game theory and decision theory can be applied in agent-based systems, from standard applications of the core elements of the theory to more cutting edge developments. The range of topics discussed in this book provide the reader with the first comprehensive volume that reflects both the depth and breadth of work in applying techniques from game theory and decision theory to design agent-based systems. Chapters include: Selecting Partners; Evolution of Agents with Moral Sentiments in an IPD Exercise; Dynamic Desires; Emotions and Personality; Decision-Theoretic Approach to Game Theory; Shopbot Economics; Finding the Best Way to Join in; Shopbots and Pricebots in Electronic Service Markets; Polynomial Time Mechanisms; Multi-Agent Q-learning and Regression Trees; Satisficing Equilibria; Investigating Commitment Flexibility in Multi-agent Contracts; Pricing in Agent Economies using Multi-agent Q-learning; Using Hypergames to Increase Planned Payoff and Reduce Risk; Bilateral Negotiation with Incomplete and Uncertain Information; Robust Combinatorial Auction Protocol against False-name Bids.

Reputation In Artificial Societies discusses the role of reputation in the achievement of social order. The book proposes that reputation is an agent property that results from transmission of beliefs about how the agents are evaluated with regard to a socially desirable conduct. This desirable conduct represents one or another of the solutions to the problem of social order and may consist of cooperation or altruism, reciprocity, or norm obedience. Reputation In Artificial Societies distinguishes between image (direct evaluation of others) and reputation (propagating meta­belief, indirectly acquired) and investigates their effects with regard to both natural and electronic societies. The interplay between image and reputation, the processes leading to them and the set of decisions that agents make on their basis are demonstrated with supporting data from agent­based simulations.

Social Order in Multiagent Systems provides an overview of current approaches, problems, and considerations related to the study of norms and institutions in the context of multiagent systems. The contributions in this volume share the assumption that norms and other social institutions are of vital importance for the development of multiagent systems and agent-mediated interaction. Both formal and computational models of norms and normative systems are presented, including formal analysis of normative concepts and foundational models of norms; agent and systems architectures for implementing norms; and implemented systems. Social Order in Multiagent Systems is an excellent reference for researchers in artificial intelligence and computer science, and can be used as text for advanced level courses in multiagent systems.

Socially situated planning provides one mechanism for improving the social awareness ofagents. Obviously this work isin the preliminary stages and many of the limitation and the relationship to other work could not be addressed in such a short chapter. The chief limitation, of course, is the strong commitment to de?ning social reasoning solely atthe meta-level, which restricts the subtlety of social behavior. Nonetheless, our experience in some real-world military simulation applications suggest that the approach, even in its preliminary state, is adequate to model some social interactions, and certainly extends the sta- of-the art found in traditional training simulation systems. Acknowledgments This research was funded by the Army Research Institute under contract TAPC-ARI-BR References [1] J. Gratch. Emile: Marshalling passions in training and education. In Proceedings of the Fourth International Conference on Autonomous Agents, pages 325–332, New York, 2000. ACM Press. [2] J. Gratch and R. Hill. Continous planning and collaboration for command and control in joint synthetic battlespaces. In Proceedings of the 8th Conference on Computer Generated Forces and Behavioral Representation, Orlando, FL, 1999. [3] B. Grosz and S. Kraus. Collaborative plans for complex group action. Arti?cial Intelli gence, 86(2):269–357, 1996. [4] A. Ortony, G. L. Clore, and A. Collins. The Cognitive Structure of Emotions. Cambridge University Press, 1988. [5] R.W.PewandA.S.Mavor,editors. Modeling Human and Organizational Behavior. National Academy Press, Washington D.C., 1998.

An Application Science For Multi-Agent Systems addresses the complexity of choosing which multi-agent control technologies are appropriate for a given problem domain or a given application. Without such knowledge, when faced with a new application domain, agent developers must rely on past experience and intuition to determine whether a multi-agent system is the right approach, and if so, how to structure the agents, how to decompose the problem, and how to coordinate the activities of the agents, and so forth. This unique collection of contributions, written by leading international researchers in the agent community, provides valuable insight into the issues of deciding which technique to apply and when it is appropriate to use them. The contributions also discuss potential trade-offs or caveats involved with each decision. An Application Science For Multi-Agent Systems is an excellent reference for anyone involved in developing multi-agent systems.

Conflicts between agents acting in a multi-agent environment arise for different reasons, involve different concepts, and are dealt with in different ways, depending on the kind of agents and on the domain where they are considered. Agents may have conflicting beliefs, conflicting goals, or may have to share limited resources. Consequently, conflicts may be expressed as mere differences, or as contradictions, or even as social conflicts. They may be avoided, solved, kept, or even created deliberately. Conflicting Agents studies conflicts in the context of multi-agent systems, i.e. artificial societies modeled on the basis of autonomous, interacting agents. This book addresses questions about types of conflicts, conflict definitions and the use of conflicts as trigger functions for activities in multi-agent systems. The book is also dedicated to questions of conflict management, resolution and avoidance, i.e. the question of how agents cope with conflicts and conflicting situations.