This book constitutes the thoroughly refereed proceedings of the 7th International Workshop on Multi-Agent-Based Simulation, MABS 2006. This was held in Hakodate, Japan, May 8, 2006 as an associated event of AAMAS 2006, the main international conference on autonomous agents and multi-agent systems. The 12 revised full papers presented together with three short papers and two invited papers were carefully reviewed and selected from 25 submissions during two rounds of reviewing.
This book constitutes the thoroughly refereed post-conference proceedings of the 21st International Workshop on Multi-Agent-Based Simulation, MABS 2021, held in May 2021 as part of AAMAS 2021. The conference was held virtually due to COVID 19 pandemic. The 14 revised full papers included in this volume were carefully selected from 23 submissions. The workshop focused on finding efficient solutions to model complex social systems, in such areas as economics, management, organizational and social sciences in general. In all these areas, agent theories, metaphors, models, analysis, experimental designs, empirical studies, and methodological principles, all converge into simulation as a way of achieving explanations and predictions, exploration and testing of hypotheses, better designs and systems and providing decision-support in a wide range of applications.
This book is devoted to investigating and developing the synergy between software engineering for multi-agent systems and agent-based social simulation; it originates from the Second International Workshop on Multi-Agend-Based Simulation, MABS 2000, held in Boston, MA, USA in July 2000, in conjunction with ICAMS 2000. Besides the thoroughly revised full papers accepted for presentation at the workshop, two invited papers and an introductory survey by one of the volume editors have been added in order to round off the scope and achieve complete coverage of all relevant topics. The book competently surveys the state of the art in the area by offering topical sections on model design issues, applications, simulating social relations and processes, and formal approaches.
Fifteen papers were presented at the first workshop on Multi-Agent Systems and Agent-Based Simulation held as part of the Agents World conference in Paris, July 4-- 6, 1998. The workshop was designed to bring together two developing communities: the multi-agent systems researchers who were the core participants at Agents World, and social scientists interested in using MAS as a research tool. Most of the social sciences were represented, with contributions touching on sociology, management science, economics, psychology, environmental science, ecology, and linguistics. The workshop was organised in association with SimSoc, an informal group of social scientists who have arranged an irregular series of influential workshops on using simulation in the social sciences beginning in 1992. While the papers were quite heterogeneous in substantive domain and in their disciplinary origins, there were several themes which recurred during the workshop. One of these was considered in more depth in a round table discussion led by Jim Doran at the end of the workshop on 'Representing cognition for social simulation', which addressed the issue of whether and how cognition should be modelled. Quite divergent views were expressed, with some participants denying that individual cognition needed to be modelled at all, and others arguing that cognition must be at the centre of social simulation.
This volume presents extended and revised versions of the papers presented at the Third International Workshop on Multi-Agent Based Simulation (MABS 2002), a workshop federated with the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2002), which was held in Bologna, Italy, in July, 2002. This workshop was the third in the MABS series. The earlier two were - ganized as workshops of the two most recent ICMAS conferences (ICMAS 1998, Paris, France and ICMAS 2000, Boston, USA). Revised versions of the papers presented at these workshops were published as volumes 1534 and 1979 in the Lecture Notes in Arti?cial Intelligence series. One aim of the workshop was to develop stronger links between those wo- ing in the social sciences and those involved with multi-agent systems. We are pleased to note that many important conferences in various disciplines such as geography, economics, ecology, sociology, and physics have hosted workshops on MABS-related topics and that many respected journals publish papers that - clude elements of MABS. But although MABS is gradually acquiring legitimacy in many disciplinary ?elds, much remains to be done to clarify the potential use of MABS in these disciplines. Researchers from these disciplines have di?erent points of view on issues such as time-frame, space, geographical scales, or- nizational levels, etc. Moreover, the interest in MABS goes beyond the scienti?c community, as MABS models have been developed and used interactively with other communities as well.
Methodological Guidelines for Modeling and Developing MAS-Based Simulations The intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, including methodological and application-oriented guidelines. This comprehensive resource reviews two decades of research in the intersection of MAS, simulation, and different application domains. It provides scientists and developers with disciplined engineering approaches to modeling and developing MAS-based simulations. After providing an overview of the field’s history and its basic principles, as well as cataloging the various simulation engines for MAS, the book devotes three sections to current and emerging approaches and applications. Simulation for MAS — explains simulation support for agent decision making, the use of simulation for the design of self-organizing systems, the role of software architecture in simulating MAS, and the use of simulation for studying learning and stigmergic interaction. MAS for Simulation — discusses an agent-based framework for symbiotic simulation, the use of country databases and expert systems for agent-based modeling of social systems, crowd-behavior modeling, agent-based modeling and simulation of adult stem cells, and agents for traffic simulation. Tools — presents a number of representative platforms and tools for MAS and simulation, including Jason, James II, SeSAm, and RoboCup Rescue. Complete with over 200 figures and formulas, this reference book provides the necessary overview of experiences with MAS simulation and the tools needed to exploit simulation in MAS for future research in a vast array of applications including home security, computational systems biology, and traffic management.
The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status. The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations. The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core. The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis. Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references. We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.
Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.
The study of multi-agent systems (MAS) focuses on systems in which many intelligent agents interact with each other. These agents are considered to be autonomous entities such as software programs or robots. Their interactions can either be cooperative (for example as in an ant colony) or selfish (as in a free market economy). This book assumes only basic knowledge of algorithms and discrete maths, both of which are taught as standard in the first or second year of computer science degree programmes. A basic knowledge of artificial intelligence would useful to help understand some of the issues, but is not essential. The book’s main aims are: To introduce the student to the concept of agents and multi-agent systems, and the main applications for which they are appropriate To introduce the main issues surrounding the design of intelligent agents To introduce the main issues surrounding the design of a multi-agent society To introduce a number of typical applications for agent technology After reading the book the student should understand: The notion of an agent, how agents are distinct from other software paradigms (e.g. objects) and the characteristics of applications that lend themselves to agent-oriented software The key issues associated with constructing agents capable of intelligent autonomous action and the main approaches taken to developing such agents The key issues in designing societies of agents that can effectively cooperate in order to solve problems, including an understanding of the key types of multi-agent interactions possible in such systems The main application areas of agent-based systems
Operational Research (OR) deals with the use of advanced analytical methods to support better decision-making. It is multidisciplinary with strong links to management science, decision science, computer science and many application areas such as engineering, manufacturing, commerce and healthcare. In the study of emergent behaviour in complex adaptive systems, Agent-based Modelling & Simulation (ABMS) is being used in many different domains such as healthcare, energy, evacuation, commerce, manufacturing and defense. This collection of articles presents a convenient introduction to ABMS with papers ranging from contemporary views to representative case studies. The OR Essentials series presents a unique cross-section of high quality research work fundamental to understanding contemporary issues and research across a range of Operational Research (OR) topics. It brings together some of the best research papers from the esteemed Operational Research Society and its associated journals, also published by Palgrave Macmillan.
