With increasing acceptance of agent-based computing, a great deal of new research related to the identification and definition of suitable models, tools, and techniques to support the development of complex Multiagent Systems (MAS) has emerged. This research, generally identified as Agent-Oriented Software Engineering (AOSE), continually proposes new metaphors, new formal modeling approaches and techniques, and new development methodologies and tools. The contributions in Methodologies and Software Engineering for Agent Systems, written by leading international researchers, bring together these diverse research results and proposals. The book is separated into six parts, providing the reader with introductory material, concepts and techniques that already provide results for practical use, and research that is still more investigative in nature. Contents......Page 6 Contributing Authors......Page 12 Foreword......Page 22 Introduction......Page 28 Part I Concepts and Abstractions of Agent-Oriented Software Engineering......Page 32 Introduction......Page 34 1. Introduction......Page 36 2. A Brief History of Software Development......Page 38 3. Agents and Multiagent Systems......Page 40 4. Agent-Based Software Development......Page 44 5. Critical Directions......Page 47 6. Conclusions......Page 48 1. Introduction......Page 50 2. Software Agents vs. Software Components......Page 51 3. Semantically Reusing Agents and Components......Page 56 4. Discussion......Page 61 1. Introduction......Page 64 2. Analysis......Page 66 3. Design......Page 72 4. Implementation......Page 86 5. Testing......Page 88 7. Conclusions......Page 92 Part II Methodologies for Agent-Based Systems Development......Page 94 Introduction......Page 96 1. Introduction......Page 100 2. Gaia in a Nutshell......Page 101 3. Gaia v.2......Page 106 4. The ROADMAP Methodology......Page 110 5. Extending Gaia with AUML......Page 115 7. Conclusions......Page 118 1. Introduction......Page 120 2. Overview......Page 121 3. Formal Tropos......Page 125 4. Socially-Based MAS Architectures......Page 129 5. Goal Models......Page 133 6. Conclusions......Page 136 1. Introduction......Page 138 3. Analysis Phase......Page 139 4. Design Phase......Page 148 5. agentTool......Page 153 7. Comparison with other Methodologies......Page 155 1. Introduction......Page 158 2. The Evaluation Framework......Page 160 3. Evaluating Gaia......Page 165 4. Evaluating Tropos......Page 169 5. Evaluating MaSE......Page 174 6. Summary and Conclusion......Page 178 Part III Special-Purpose Methodologies......Page 182 Introduction......Page 184 1. Introduction......Page 188 2. ADELFE Methodology Overview......Page 189 4. Final Requirements......Page 192 5. Analysis......Page 194 6. Design......Page 196 7. ADELFE Tools......Page 203 8. Comparison with other Methodologies......Page 204 9. Conclusion......Page 205 1. Introduction......Page 208 2. The MESSAGE Methodology......Page 209 3. Analysis/Design Travel Agent Case-Study......Page 214 4. Considerations on Low-Level Design......Page 222 5. Evaluation of MESSAGE......Page 224 6. Conclusions......Page 225 1. Introduction......Page 226 2. The SADDE Methodology......Page 227 4. Step 1: The EBM......Page 230 5. Step 2: The Electronic Institution......Page 234 6. Step 3: The ABM......Page 237 8. Cycle P4 through Evolutionary Computing......Page 241 9. Conclusions......Page 245 1. Introduction......Page 248 2. System Specification......Page 251 3. Architectural Design......Page 253 4. Detailed Design......Page 257 5. Tool Support......Page 259 6. Experiences with Using Prometheus......Page 261 7. Related Work......Page 262 8. Future Work......Page 265 Part IV Tools and Infrastructures for Agent-Oriented Software Engineering......Page 266 1. Introduction......Page 268 2. Agent UML Purpose......Page 269 3. Current Work in Agent UML......Page 270 4. Future Directions in Agent UML......Page 283 5. Conclusion......Page 287 1. Introduction......Page 290 2. FIPA......Page 291 3. FIPA-Compliant Agent Infrastructures......Page 293 4. JADE......Page 295 5. Conclusions......Page 303 1. Introduction......Page 304 2. Coordination in MAS......Page 305 3. Infrastructures for MAS Engineering......Page 309 4. Modelling Coordination Infrastructures with Activity Theory......Page 314 5. Engineering MAS with Coordination Infrastructures......Page 321 6. An Example of a Coordination Infrastructure......Page 324 7. Discussion......Page 326 Part V Non Traditional Approaches to Agent-Oriented Software Engineering......Page 328 Introduction......Page 330 1. Introduction......Page 334 3. Developmental Biology as an Inspiration......Page 336 4. Towards Programming Languages......Page 340 5. Pervasive Computing......Page 346 1. Introduction......Page 352 2. Characterization of Emergence in Synthetic Systems......Page 356 3. An Example of a MAS Technology using Emergence......Page 358 4. Flood Forecast by Cooperative Self-Organizing Agents......Page 362 5. Software Engineering Requirements for Self-Organizing MAS......Page 368 6. Conclusion......Page 371 1. What is Swarming?......Page 372 2. Where would You Want to Use Swarming?......Page 380 3. Why does Swarming Work?......Page 384 4. How can We Apply these Principles in Engineered Systems?......Page 395 5. Conclusion and Prospect......Page 406 1. Introduction......Page 408 2. Open Computational Systems......Page 410 3. Online Engineering......Page 413 4. Methodological Benchmarking......Page 417 5. Concluding Remarks and Future Work......Page 419 Part VI Emerging Trends and Perspectives......Page 422 Introduction......Page 424 1. Introduction......Page 426 2. Examples on Ubiquitous Computing......Page 428 3. Background......Page 429 4. Dimensions of Ubiquitous Computing......Page 432 5. Contributions of Agents to Ubiquitous Computing......Page 435 6. Conclusion......Page 442 1. Introduction......Page 444 2. The Grid and Bioinformatics......Page 445 3. Agents in Bioinformatics Grids......Page 447 4. Agent-Based Service Discovery for Grid Computing......Page 450 5. Architecture Design......Page 454 6. Performance Analysis......Page 457 7. Related Work......Page 459 8. Conclusion and Future Work......Page 460 1. Introduction......Page 462 2. Agents as a New Modeling Paradigm......Page 464 3. Methods for Building Multiagent Systems......Page 466 4. Tools for the Implementation, Deployment and Execution......Page 472 5. Application Opportunities......Page 478 6. A Roadmap for Agent-Oriented Software Engineering......Page 479 7. Conclusions......Page 481 References......Page 482 E......Page 534 S......Page 535 Z......Page 536 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.
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.
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multi-agent Systems Implement Complex Open Systems, Such As Electronic Marketplaces And Military Coalition Support Systems. This Collection Of Ten Papers From A June 2000 Workshop On Norms And Institutions In Multi-agent Systems Considers Some Of The Questions Related To Definitions, Models, And Architectures Currently Arising In The Field. Topics Include Multi-agent Benevolence As A Societal Norm, A Contractual Agent Society Prototype, The Effectiveness Of Incentives In Achieving Social Order, The Connection Between The Tasks And Right System And The Behavioral System Of Social Practices, And Computational Ecosystems In Home Health Care. Annotation C. Book News, Inc., Portland, Or (booknews.com)
the Field Of Socially Intelligent Agents (sia) Is A Fast Growing And Increasingly Important Area That Comprises Highly Active Research Activities And Strongly Interdisciplinary Approaches. Socially Intelligent Agents, Edited By Kerstin Dautenhahn, Alan Bond, Lola Cañamero And Bruce Edmonds, Emerged From The Aaai Symposium Socially Intelligent Agents - The Human In The Loop.
The Book Provides 32 Chapters, Written By Leading Sia Researchers, Addressing Topics Such As: Social Robotics, Embodied Conversational Agents, Affective Computing, Anthropomorphism, Narrative And Story-telling, Social Aspects In Multi-agent Systems, New Technologies For Education And Therapy, And More. This Breadth Of Topics Covered In Socially Intelligent Agents Provides The Reader With A Comprehensive Look At Current Research Activities In The Area.
Socially Intelligent Agents Serves As An Excellent Reference For A Wide Readership, E.g. Computer Scientists, Roboticists, Web Programmers And Designers, Computer Users, Cognitive Scientists, And Other Researchers Interested In The Study Of How Humans Relate To Computers And Robots, And How These Agents In Return Can Relate To Humans. This Book Is Also Suitable As Research Material In A Variety Of Advanced Level Courses, Including Applied Artificial Intelligence, Autonomous Agents, Human-computer Interaction, Situated, Embodied Ai.
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.
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.
"Socially Intelligent Agents serves as an excellent reference for a wide readership, e.g., computer scientists, roboticists, web programmers and designers, computer users, cognitive scientists, and other researchers interested in the study of how humans relate to computers and robots, and how these agents in return can relate to humans. This book is also suitable as research material in a variety of advanced level courses, including Applied Artificial Intelligence, Autonomous Agents, Human-Computer Interaction, Situated and Embodied Al."--BOOK JACKET. In the last 10 years, research on distributed artificial intelligence (DAI) and on systems of several more or less autonomous agents, called multi-agent systems (MAS), has received much interest in the domain of artificial intelligence.
