Autonomous Agents and Multi-Agent Systems 2002

Tutorial location
Tutorial schedule
Tutorial details

Tutorial location

Tutorials and workshops will take place on 15th and 16th of July at the Faculty of Engineering
(Facoltà di Ingegneria) of the University of Bologna, in Via Risorgimento 2, just outside of the city centre.

The best way to reach the Faculty of Engineering is to reach Porta Saragozza (at the South-West vertex of the Walls of the Old Town) by taxi, bus (line 20 from the city center, line 32 from the train station), or walking (ten minutes from the city center). Then, climb the hill through Via Risorgimento, find the buildings of the Faculty on the top of the hill, and follows the signs.

All the tutorials will be located in the DEIS building of the Engineering Faculty. In particular, Room 4.1 is located at the ground floor, while Rooms 5.1, 5.3, 5.4, 5.5 are located at the first floor of the DEIS building. Also, please notice that both the DEIS and the Main building of the Engineering Faculty are actually different portions of the same big building, so that attendants can easily move among different tutorials and workshops fast and easily.

Tutorial schedule

	15 July 2002			16 July 2002
Room	5.4	5.1	5.3	5.5	5.3	4.1	5.1
8:30	T1	T2	T3	T6	T7	T8	T9
10:30
coffee break
11:00
12:30
lunch break
13:30		T4	T5	T10	T11	T12	T13
15:30
coffee break
16:00
17:30

Tutorial details

T1
Collaborative Multi-agent Systems (FULL DAY)
Barbara Grosz, Charlie Ortiz, Milind Tambe
Collaborative agent systems are critical in a vast range of applications, in virtual environments for training and education, in improving human-computer interaction and organizational productivity, in applications in disaster rescue, space, military, and other spheres. Such collaborative systems are within reach thanks to progress in our understanding of rationality, both collective and individual. This tutorial will describe both the major theoretical advances that can support the principled designs and analysis of such systems as well as describe implementations based on these theories. The tutorial will begin with an overview of rationality: what it means for an agent to be rational and how this can be reflected in agent designs. This will include a brief review of models of mental state: for example, the representation and role of intentions and the relation of intentions to other attitudes such as that of belief. Then we will consider information flow within agent architectures, emphasizing considerations of resource-boundedness and the ways this affects formalizations and system designs. The tutorial will then examine a range of approaches to modeling the collaborative behavior of a group of agents on a joint task. Two broad classes of formal computational models will be presented and examined in the light of major philosophical approaches. The first class of models, prescriptive in nature, are formalized using modal logic. They require the introduction of new notions of intention, ability, and helpful behavior. These new notions will be examined, as will ways to model stages of partiality in joint planning processes. The second class of models, focused on analysis, are formalized using markov decision processes (MDPs). We will introduce distributed partially observable MDPs, and the complexity efficiency analysis made possible by these models. The tutorial will also examine in detail practical, real-world collaborative multiagent systems developed based on models of collaboration, explaining strengths and the weaknesses in existing formal models. We will also examine adjustable autonomy, a critical issue for collaborative systems involving agent-human interactions. Interested participants may attend our tutorial in the morning (half day), in the afternoon (half day) or the full day. Researchers familiar with theory and interested in practical aspects of collaboration may attend the second half in the afternoon, while researchers especially interested in BDI theories may wish to attend only the first half. Tutorial contents The tutorial will cover the following areas: (1) motivations for collaboration; (2) BDI theories and agent architectures; (3) theories of collaboration; (4) practical applications of agent systems, including agent-human interactions and adjustable autonomy; (5) decision theoretic agents; (6) negotiation in collaborative systems; (7) and demonstrations of select collaborative systems. Target audience and necessary background This tutorial is suitable for a general AI audience. Knowledge of AI planning would be helpful. It should be of interest to: researchers in distributed AI; those interested in the theoretical aspects of collaboration; and those interested in designing and building collaborative information systems, user interfaces, and planning systems. Information about the lecturers Barbara Grosz is the Higgins Professor of Natural Sciences in the Division of Engineering and Applied Sciences and Dean of Science of Radcliffe Institute, Harvard University and is a past president of AAAI. Her research addresses fundamental problems in modeling collaborative activity and in developing computer systems able to collaborate with each other and their users. She is one of the developers of the SharedPlans model of collaboration. She is extending this model and using it to construct collaborative interfaces and computer agents that work together in teams. Charlie Ortiz is Program Manager of Collaboration Science and Technology at the AI Center of SRI International. His research centers on understanding the connections between mind and action, from both a planning and an explanatory perspective. At SRI he leads projects in distributed robotics and negotiation for multiagent systems. As a postdoctoral fellow at Harvard, his research focussed on models of collaboration. His PhD in computer science from the University of Pennsylvania was for his work on causation. Milind Tambe is an Associate Professor of Computer Science at University of Southern California (USC), and a project leader at USC's Information Sciences Institute. He received his Ph.D. in 1991 from the School of Computer Science at Carnegie Mellon University. His interests are in the areas of multi-agent systems, specifically multi-agent teamwork, negotiation, agent modeling and adjustable autonomy, and he has published extensively in these areas. He has constructed several large-scale, real-world agent teams, based on a reusable teamwork model called STEAM that applies across these applications. More recent work has involved a formal analysis of teamwork using distributed partially observable markov decision processes.

T2
Market Clearing Algorithms
Tuomas Sandholm
The last three years have witnessed a leap of improvement in market clearing algorithms both for traditional market designs and entirely new market designs enabled by advanced clearing technology. This tutorial covers the computational implications of different market designs and presents algorithms for clearing markets optimally and approximately. Auctions, reverse auctions, and exchanges (many-to-many auctions) are covered. Both theoretical and experimental results are presented. Multi-item and multi-unit markets will be a key focus. Computational implications of different classes of side constraints will be presented. Bid types covered include price-quantity bids, different shapes of supply/demand curves, and combinatorial bids. A new method for selective preference elicitation for combinatorial markets is presented. Target audience and necessary background No prior knowledge of markets is assumed. A basic familiarity with algorithms and NP-completeness would be helpful. Information about the lecturer Tuomas Sandholm is Associate Professor of computer science at Carnegie Mellon University. He received the Ph.D. and M.S. degrees in computer science from the University of Massachusetts at Amherst in 1996 and 1994. He earned an M.S. (B.S. included) with distinction in Industrial Engineering and Management Science from the Helsinki University of Technology, Finland, in 1991. He has eleven years of experience building electronic marketplaces. Several of his systems have been commercially fielded. He has published over 125 technical papers, and received numerous academic awards including the inaugural ACM SIGART Autonomous Agents Research Award and the NSF Career award.

T3
Social Interaction with Embodied Agents
W. Lewis Johnson
This tutorial will acquaint the participants with current methods for creating embodied agents capable of social interaction with users. It has been well established by Reeves, Nass, and others that people react to computers in a similar way to the way that they interact people, i.e., they interact socially with computers. Embodied agents exploit this tendency by presenting a human-like appearance. But appearance alone is not sufficient: if agents are unable to interact socially in an effective manner with people, it can engender negative impressions and frustration in people. The tutorial will review methods for generating adaptive behavior in agents, and then focus on the requirements for effective social interaction. These include modeling attitudes, affect, and personality in agents, modeling face-to-face communication, modeling user responses, and engaging in interactional tactics. Collaboration in human-agent teams will also be discussed. Particular emphasis will be placed on educational applications, where social intelligence can yield practical benefits. Expert tutors are able to interact with learners at both an affective and a cognitive level. Agents that are able to gauge learner affect and reactions, and are able to develop a social relationship with learners, have the potential of improving the effectiveness of educational software. Target audience and necessary background The course will be designed to be understandable by beginners, although participants with an advanced background in embodied agents and human-agent interaction should also benefit. Information about the lecturer Lewis Johnson a Senior Project Leader at the University of Southern California / Information Sciences Institute, where he directs the Center for Advanced Research in Technology for Education. His particular area of research interest is in the use of embodied agents for education and training applications. He is program co-chair of the AAMAS 2002 conference, a member of the Steering Committee for the International Conferences on Autonomous Agents, and is chair of the selection committee for the SIGART Autonomous Agents Research Award. Dr. Johnson has presented a number of tutorials and invited talks on autonomous agent topics around the world, including the 2002 AmericasÕ Agent School.

T4
Agents, Middleware, and the Grid
Omer Rana, Michael Schroeder
Recent advances in information technology and its use, such as component based software development, high speed networks, standardisation of interfaces to databases and data repositories, virtual machines and cluster computing, public domain and community software licensing arrangements, on-demand (on-use) software payment schemes, and network aware interfaces and visualisation have the potential to transform the capability and modalities of scientific research by providing transparent, intuitive, timely, effective and efficient access to distributed, heterogeneous and dynamic resources. These resources include computational facilities, applications, visualisation, data and experimental facilities, integrated and accessible as a single resource over the Internet - the Grid. To make effective utilisation of resources across a Grid that spans organisational boundaries, it is imperative that the underlying infrastructure support intelligence. Intelligent software is required to undertake resource and service management, service discovery, service aggregation/decomposition, and support performance management. Commercial systems will also require the underlying infrastructure to respect site autonomy, and particular site specific policies on usage. Thus, many solutions developed in the agents community are applicable to the grid and the grid can serve as a practical testbed for many agent concepts and theories. In this tutorial we will present example problems that require Grid solutions — and outline reasons why the Grid is necessary. We also survey Grid middleware such as CORBA, RMI, PVM, MPI, and mobile agents — and outline reasons why the agent based approach is suitable for Grid computing. We briefly explore emerging areas which are likely to impact Grid applications — such as WebServices and Peer-2-Peer computing. We will cover Grid infrastructure for resource discovery, resource allocation, and security as catered for in platforms like Globus (such as the Open Grid Services Architecture (OGSA)) and others, and discuss advanced topics, which are particularly relevant for agent research, such as service discovery, service composition, load-balancing, trading and brokering. Target audience and necessary background The tutorial assumes familiarity with basic programming concepts. Information about the lecturers Omer Rana is a Senior Lecturer in the Department of Computer Science at Cardiff University, and the Associate Director for the Welsh E-Science/Grid Centre. He has delivered university and industry courses on Distributed Systems and Distributed Multi-Agent systems over the last 5 years. He has published over 50 papers, and has been involved in the public understanding of science, working with BBC radio and television, Channel 4 and the Discovery Channel as part of ScienceLine. In 2000 he won an award from the Daily Telegraph for his article on "Information Ants". His areas of research include high performance distributed computing, and scalable multi-agent communities. He has organised various conferences and workshops, and is on the editorial boards of "Concurrency and Computation: Practice and Experience" and "Scientific Programming" journals. He co-chairs a research group on the Global Grid Forum, and also participates on the UK Grid Engineering Task Force. Michael Schroeder is a Senior Lecturer at the Department of Computing at City University London. He teaches courses on Distributed Systems and Software Agents and carries out research in software agents. He has published over 60 articles including a monograph, two patents and 13 journal articles, supervises five PhD students/RAs and manages nationally and EU-funded projects on building information agents which integrate information, deal with conflicts, and visualise the data to the user. He is joint winner of the Cambridge University Entrepreneurs Competition in 2000 and co-chaired two AISB symposia and a workshop on rule mark-up langugages.

T5
Empirical Methods for Analysis of Agent Systems
Paul R. Cohen
How do you know that an agent system behaves the way it is supposed to? How can you discover unexpected but interesting behaviors? How might you compare two communication protocols, or evaluate the effects of a motivational system, or model the contributions of environmental factors to performance? These kinds of questions motivate empirical methods, which include techniques for visualizing data, discovering patterns, designing experiments, testing hypotheses, and building models. The methods in this tutorial are statistical and include exploratory data analyses and visualizations, experiment design tips and techniques, statistical tests and methods for continuous, categorical, and time series data; including t tests, analysis of variance, regression analysis, log-linear models and contingency tables; all applied to complex agent systems. The principal theme of the tutorial is that understanding agent systems is equivalent to assigning portions of the variance of performance measures to causal factors in the environment, the agent's task, and its architecture. Information about the lecturer Paul Cohen is Professor of Computer Science at the University of Massachusetts. He has published widely on empirical methodology, including the book "Empirical Methods for Artificial Intelligence," (MIT Press, 1995).

T6
Rational Action in Autonomous Agents
Michael Wooldridge, Simon Parsons
The past decade has been witness to a rapid growth of interest in the problems surrounding the design of rational autonomous agents. For many researchers, this is now the defining problem of the AI endeavour. Our aim in this tutorial is to show how computational agents can be designed that can make effective decisions given only limited resources. After attending this tutorial, an attendee will: understand the concept of an autonomous agent; understand basic economic and decision-theoretic approaches to rational action in autonomous agents; understand the limitations of naive utility maximising approaches to rational action in resource-bounded agents; understand the main alternatives to utility maximisation approaches, including bounded-optimality, decision-theoretic planning, and partially observable Markov decision processes; understand the belief-desire-intention (BDI) model of agency, as a computational approach to rational decision making. Tutorial contents Following an introduction to the basic idea of autonomous agents, we survey the main theoretical approaches to rational decision making, in which rational decision-making is viewed as utility maximisation. After discussing the limitations of such approaches, we introduce the key techniques proposed in the literature for overcoming these problems. We focus in particular on the belief-desire-intention (BDI) model of agency, which we illustrate by means of examples from mobile robotics. Target audience and necessary background The tutorial is intended for delegates with a basic grounding in AI, (including such basic issues as search and knowledge representation) but no knowledge of agents, decision theory, rational action, bounded rationality, or the BDI model. Information about the lecturers Michael Wooldridge is Professor of Computer Science in the Department of Computer Science at the University of Liverpool. He has been active in the research and development of multi-agent systems for ten years, gaining his PhD for work in the theoretical foundations of multi-agent systems from the University of Manchester, UK in 1992. Prof Wooldridge has published many articles in the theory and practice of agent-based systems, and has edited eight books in the area. He has served on many program committees for conferences and workshops in the area, and serves as an associate editor of the International Journal of Autonomous Agents and Multi-Agent Systems (Kluwer), and an editorial board member for the Journal of Applied AI (Taylor & Francis). He is coordinator of AgentLink, the ESPRIT-funded European Network of Excellence in the area of agent-based computing (see http://www.AgentLink.org/). Simon Parsons is a Reader in the Department of Computer Science at Liverpool University. Dr Parsons received his PhD from the University of London in 1993 for work on non-numerical approaches for decision making in intelligent systems, and subsequently spent two years as a post-doctoral fellow at the Imperial Cancer Research Fund. Here he became interested in theoretical and practical aspects of argumentation and its use as a non-numerical means of making decisions under uncertainty. A focus of this work was clarifying the relationship between argumentation and probability theory, which paved the way for current research into the use of argumentation as a normative approach to decision making. In 1995 Dr Parsons moved to Queen Mary and Westfield College (QMW) as a Lecturer in the Department of Electronic Engineering, and became involved in adapting systems of argumentation, which were initially developed for lone intelligent agents, for use in a multi-agent context. In particular, this work has concentrated on the use of argumentation as a mechanism for negotiation. He moved to Liverpool University at the end of 1999. Dr Parsons is the principal investigator on the EPSRC funded project Qualitative Methods for Reasoning under Uncertainty, and heads Liverpool's effort on the EC funded project "Sustainable Lifecycles for Information Ecosystems". He is also in charge of QMW's work on the EC funded ACTS project "Multi-agent Architecture for Distributed-In Load Control". He has written over sixty papers on techniques supporting decision making in intelligent systems, co-edited two collections on the same subject, and has a monograph in press. Dr Parsons is the editor of the Knowledge Engineering Review, published by Cambridge University Press, and was the recipient of a 1998 Younger Engineers Achievement Medal, awarded by the IEE, for his work in informatics.

T7
Fundamentals of Web Services
Munindar P. Singh, Michael N. Huhns
Web services have been garnering much attention lately in the industry and from the research community. Everyone agrees about their importance to information technology architectures and applications. Unfortunately, much of the attention on web services has been focused on low-level, infrastructural matters, sometimes down to encoding syntaxes. However, to effectively design and use web services requires an understanding of deeper concepts of architecture, knowledge representation, programming models, communications, interaction, compliance, and trust. These concepts have been developed in diverse parts of computer science, especially, heterogeneous databases, distributed computing, artificial intelligence, and multiagent systems. This tutorial describes web services at a conceptual level. It provides the fundamentals necessary to understand key challenges and evaluate possible approaches. This tutorial highlights the best practices of web services and motivates the key trade-offs that sometimes underlie industry hype. In this manner, it gives the essential background for anyone planning to develop, use, or research web services. Attendees are encouraged to also register for a companion tutorial on "In Depth Techniques, Technologies and Tools for Web Services," taught by Katia Sycara and Terry Payne. Information about the lecturers Munindar P. Singh is an associate professor in computer science at North Carolina State University. His research interests include multiagent systems and web services with applications in e-commerce and personal technologies. Munindar's research has been recognized with awards and sponsorship by the National Science Foundation, IBM, Cisco Systems, and Ericsson. Munindar is the editor-in-chief of IEEE Internet Computing, and a member of the editorial board of the Journal of Autonomous Agents and Multiagent Systems. He serves on the steering committee for the IEEE Transactions on Mobile Computing. Michael N. Huhns is a professor in computer science and engineering at the University of South Carolina, where he also directs the Center for Information Technology. His research interests are in the areas of distributed artificial intelligence, machine learning, enterprise modeling, and software engineering. Mike is an associate editor for the Journal of Autonomous Agents and Multiagent Systems. He is on the editorial boards of IEEE Transactions on Mobile Computing, IEEE Internet Computing, International Journal on Intelligent and Cooperative Information Systems, and Journal of Intelligent Manufacturing. He is on the Advisory Board for the First International Conference on Multiagent Systems, 1995, and has been on the Advisory Boards for several of the International Workshops on Distributed Artificial Intelligence.

T8
Reputation Mechanisms in Multiagent Systems
Chris Dellarocas, Rosaria Conte
An important challenge in open multi-agent environments is how to induce cooperation and good behaviour among independently developed and inherently selfish autonomous agents. For example, in electronic markets, selfish trader agents have incentives to cheat by misrepresenting the true quality of their services, defaulting of promises, etc. Online reputation mechanisms are emerging as a promising and efficient trust building mechanism in such settings. The proper design and evaluation of such mechanisms is a surprisingly complex problem that requires insights and tools from a variety of disciplines, including computer science, game theory, social and cognitive sciences. Tutorial contents This tutorial summarizes the state-of-the-art in reputation mechanism research and applications. An extensive literature from the fields of game theory, multi-agent systems, social theory, experimental cognitive psychology, social simulation, and sociobiology will be summarised and exemplars from each field will be discussed. A cognitive model of reputation will be presented. Applications in the field of agent-mediated interaction, with special reference to e-commerce, personalised assistants, believable agents and multi-agent systems will be addressed. Finally, the game theoretic and simulation research carried on within the presenters respective research groups will be analysed. Future directions of research will be discussed. Target audience and necessary background Familiarity with elementary game theory and cognitive modeling concepts will be helpful but not necessary. Information about the lecturers Chrysanthos Dellarocas is Associate Professor at MIT's Sloan School of Management. He holds a Ph.D. in Computer Science from MIT. He is the co-Director of the Robust Open Multi-Agent Systems (ROMA) research group at MIT Sloan. Current focal points of his work include the design of online institutions for producing trust in online markets. He has published three university-level textbooks and over 40 refereed research papers. His recent editorial and review activities include organizing two recent workshops on Norms and Institutions in Multiagent Systems and serving as an associate editor of the Electronic Commerce Research Journal. He is a recent recipient of the NSF CAREER Award for his work in multiagent systems. Rosaria Conteis currently Head of the "AI, Cognitive and Interaction Modelling" Division at ISTC (Institute of Cognitive Sciences and Technologies) of the Italian Research Council, and is teaching at the University of Siena. She is active in the field of Multi-Agents Systems, and has contributed to the development of Social Simulation in Europe. Her research experience ranges from formal modelling to natural and artificial experiments. Former Coordinator of the ABSS (Agent-Based Social Simulation) Special Interest Group in AgentLink Network of Excellence, she is involved in several EU projects under the 5th framework. Her research interests also include organisational theory and design, and cultural and social evolution.

T9
Interaction Protocol Engineering for MAS
Marc-Philippe Huget, Jean-Luc Koning
The aim of this tutorial is to help attendees in designing interaction protocols for multiagent systems. After a brief description of what interaction in multiagent systems means, we will consider the full scope of interaction protocol engineering. This stems from communication protocol engineering and covers the design cycle from analysis to conformance testing. The core part of this tutorial will be devoted to a detailed explanation of the different engineering stages: (1) the analysis of the requirements, (2) the formal description of protocols, (3) the validation of properties on these protocols, (4) the protocol synthesis and (5) the conformance testing that checks whether the program behaves like the protocol. Target audience and necessary background No special background is required to attend this tutorial. Numerous example will be provided all along the lecture. By the end of the tutorial, attendees will know how to design interaction protocols given a formalism and will be able to perform protocol checking. Interaction is definitely a major aspect in the design of multiagent systems. This tutorial will gives a complete view of it. Information about the lecturer Marc-Philippe Huget is currently working on the validation of communication languages and protocols in multiagent systems. He dedicated his PhD thesis to interaction protocol engineering. Jean-Luc Koning has been working in the domain of interaction since 1993. He specialized in formal definition of protocols and applications to mediation and electronic commerce.

T10
In Depth Techniques, Technologies and Tools for Web Services
Katia Sycara, Terry Payne
Web services are being hailed as the Next Big Wave of innovation in e-commerce and B2B integration. Recent industrial interest in such services, and the availability of tools and standards to enable automated invocation of business functionality through message exchange (e.g. SOAP, UDDI, WSDL, WSFL, .NET etc) holds the promise of fast progress in this area. The web service initiatives in industry, government and research labs are many, diverse and for the most part uncoordinated. This tutorial will take an in-depth look at the current state of the art in Web Services and sort through the increasing and confusing array of relevant tools, languages and theories both from academia and industry. The tutorial will also present and discuss business models for web services and their potential for business value added. Many examples to illustrate the described concepts, techniques, tools and their use will be presented. More importantly, the tutorial will discuss limitations of current technologies and present value added advanced concepts, such as distributed service composition, semantic web enabled web services, agent-mediated web services, as well as open issues that must be addressed with emphasis on agent researcher contributions. Information about the lecturers Katia Sycara is a Professor in the School of Computer Science at Carnegie Mellon University. and director of the Advanced Agent Technology Laboratory. She holds degrees from Brown University, University of Wisconsin and Georgia Institute of Technology. She has been conducting and directing research on multiagent systems and their applications in different areas, ranging from financial portfolio management, e-commerce and crisis action management. Sycara is a founding member of the International Foundation of Multiagent Systems. a founding Editor-in Chief of the Journal on “Autonomous Agents and Multi-Agent Systems”, Area Editor for AI and Management Science for the journal “Group Decision and Negotiation”, on the editorial board of the journals “The Semantic Web”, “AI in Engineering” and “Concurrent Engineering, Research and Applications” and on the Kluwer book series on Multiagent Systems. She is the recipient of the 2002 ACM/SIGART Autonomous Agents Research Award. Terry Payne is a Project Scientist at the Robotics Institute at Carnegie Mellon University. He holds a BSc. in Computer Systems Engineering from the University of Kent at Canterbury, UK, and an MSc and PhD in Artificial Intelligence from the University of Aberdeen, Scotland. He is currently engaged in research on service and agent discovery, coordination, and interoperation of agents and web services through the Darpa Agent Markup Language (DAML) and the Semantic Web.

T11
Individuals, Markets, and Teams: A Critical Review of Coordination Mechanisms
Mark Klein
One of the key challenges involved in developing effective multi-agent systems is figuring out how the agents coordinate their activity, i.e. decide which agent does what when using what resources in order to efficiently handle the tasks given. The objective of this tutorial is to critically review the current state of the art of multi-agent coordination mechanisms, and help participants better understand the key challenges and emerging solutions that are being identified by artificial intelligence and related fields. This will include examining the four main classes of coordination mechanisms (those modeled on individuals, markets, teams and swarms) as well as approaches that are emerging to deal with coordination breakdowns (i.e. exceptions). Target audience and necessary background This tutorial is designed for researchers, advanced developers and technical managers interested in understanding how coordination technology can be used in multi-agent systems. It assumes only basic familiarity with the concept of distributing computation across multiple cooperating entities. Information about the lecturer Mark Klein is a Principal Research Scientist in the MIT Sloan Center for Coordination Science. His research addresses artificial intelligence based support for multi-agent problem solving, with a focus on collaborative design, negotiation, and exception handling. He has published over 60 journal articles, conference papers and book chapters on these topics, and has developed several major systems for conflict management, design rationale capture and workflow management.

T12
Trust Delegation and Autonomy: Foundations for Virtual Societies
Rino Falcone, Onn Shehory
The tutorial will address trust, delegation and autonomy, which are basic constructs of the social paradigm of modern AI. This paradigm will be introduced in the tutorial, focusing on its relevance to multi-agent systems. In addressing trust, we will analyse two main approaches to it: socio-cognitive and game-theoretical. Main topics: Importance of trust for interaction among autonomous agents; Game Theoretical approach to trust; Socio-Cognitive approach to trust; Relationships among trust, autonomy, and control; Trust in rational decision and cooperation; Trust, autonomy and delegation are among the foundations of agent societies. Thus, a clear presentation and analysis of the basic elements of social intelligence, and in particular of the notion of trust, should be very interesting for AAMAS attendants. Target audience and necessary background This tutorial will be accessible to all AAMAS-02 attendees. It requires interest in theoretical foundations of agenthood, and acquaintance with the agent paradigm. Information about the lecturer Rino Falcone has published several works on trust, delegation, and autonomy. He has organized several conferences and in particular in the last four years the "Deception, Fraud and Trust in Agent Societies" Workshop c/o the Autonomous Agents Conference. Onn Shehory has a decade of experience in game-theoretical aspects of multi-agent systems. He has published multiple papers, some on trust-related issues, and organized several scientific meetings on agents.

T13
Agent-based Analysis of Dynamics in Biological, Cognitive, and Organizational Domains
Catholijn M. Jonker, Jan Treur
Within biological, cognitive, and organisational domains, often multiple interacting processes occur with dynamics that are hard to handle. For example, modelling the dynamics of intracellular processes, internal mental dynamics, and organisational dynamics pose real challenges for biologists, cognitive scientists and organisation theorists. Currently differential equations are among the techniques used to address this challenge, with limited success. Within these disciplines it is felt that more abstract modelling techniques are required to cope with the complexity. Agent-based modelling makes the inherent complexity of the dynamics of multiple, interacting active processes manageable by choosing an appropriate level of abstraction in describing them. It offers structuring of a dynamic phenomenon into: internal processes within an agent, externally observable behaviour of an agent, and organisations of multiple agents. For each of these aggregation levels techniques are available for specification of dynamic properties, simulation, and formal analysis of the dynamics. Moreover, relations between dynamic properties at different levels can be identified, such as are certain dynamic properties observed and specified at the level of agent behaviour entailed by a specific agent model for internal dynamics? which dynamic properties of agent behaviour fit in a certain role within a given organisation model? does an observed trace of dynamics of an agent or an organisation fulfil a specified dynamic property? if an organisation does not show appropriate dynamics, which part is to blame? Within this tutorial such questions are addressed. A methodological perspective is presented on the basis of a number of realistic case studies: e.g., bacterial behaviour, Call Center organisation, cooperating information agents, BDI-agents. Target audience and necessary background No specific prerequisite knowledge is required. Information about the lecturer Both lecturers have extensive experience in agent modelling methodology applied within different application domains. More information on the lecturers: http://www.cs.vu.nl/~jonker, http://www.cs.vu.nl/~treur. Further Information More background information for this tutorial: http://www.cs.vu.nl/~wai/AAMAS02tutorial/.