الصفحة 1
الصفحة 1
Multi-Agent and Multi-Agent-Based Simulation ; Joint Workshop MABS 2004
The aim of the workshop was to provide a forum for work in both appli- tions of multi-agent-based simulation and the technical challenges of simulating large multi-agent systems (MAS). There has been considerable recent progress in modelling and analyzing multi-agent systems, and in techniques that apply MAS models to complex real-world systems such as social systems and organi- tions. Simulation is an increasingly important strand that weaves together this work. In high-risk, high-cost situations, simulations provide critical cost/benefit leverage, and make possible explorations that cannot be carried out in situ: – Multi-agent approaches to simulating complex systems are keytools in interdisciplinary studies of social systems. Agent-based social simulation (ABSS) research simulates and synthesizes social behavior in order to understand real social systems with properties of self-organization, scalability, robustness, and openness. – In the MAS community, simulation has been applied to awide range of MAS research and design problems, from models of complex individual agents - ploying sophisticated internal mechanisms to models of large-scale societies of relatively simple agents which focus more on the interactions between agents.
Methodological Investigations in Agent-Based Modelling : With Applications for the Social Sciences
Examines the methodological complications of using complexity science concepts within the social science domain. The opening chapters take the reader on a tour through the development of simulation methodologies in the fields of artificial life and population biology, then demonstrates the growing popularity and relevance of these methods in the social sciences. Following an in-depth analysis of the potential impact of these methods on social science and social theory, the text provides substantive examples of the application of agent-based models in the field of demography. This work offers a unique combination of applied simulation work and substantive, in-depth philosophical analysis, and as such has potential appeal for specialist social scientists, complex systems scientists, and philosophers of science interested in the methodology of simulation and the practice of interdisciplinary computing research.
Agent-Based Simulation : From Modeling Methodologies to Real-World Applications; Post Proceedings of the Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems 2004
Agent-based modeling/simulation is an emerging field that uses bottom-up and experimental analysis in the social sciences. Selected research from that presented at the Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems 2004, held in May 2004 in Kyoto, Japan, is included in this book. The aim of the workshop was to employ the bottom-up approach to social and economic problems by modeling, simulation, and analysis using a software agent. This research area is an emerging interdisciplinary field among the social sciences and computer science, attracting broad attention because it introduces a simulation-based experimental approach to problems that are becoming increasingly complex in an era of globalization and innovation in information technology. The state-of-the-art research and findings presented in this book will be indispensable tools for anyone involved in this rapidly growing discipline.
Agent-Based Modeling Meets Gaming Simulation
Provides a good example of the diverse scope and standard of research achieved in simulation and gaming today. The theme of the special session at ISAGA2003 was Agent-Based Modeling Meets Gaming Simulation. Nowadays, agent-based simulation is becoming very popular for modeling and solving complex social phenomena. It is also used to arrive at practical solutions to social problems. At the same time, however, the validity of simulation does not exist in the magni?cence of the model. R. Axelrod stresses the simplicity of the agent-based simulation model through the “Keep it simple, stupid” (KISS) principle: As an ideal, simple modeling is essential.
Agent-based modeling : The Santa Fe Institute artificial stock market model revisited
An excellent reference to both the learning, and empirical literature in finance." (Krzysztof Piasecki, Zentralblatt MATH, Vol. 1141, 2008) "Norman Ehrentreich was one of the daring few to take on the model, and he has summarized his work and findings in this excellent book. … It is useful primer for anyone interested in getting started in the area of agent-based finance. … It is essential reading for anyone interested in the dynamics of the SFI market in particular, but I also recommend it for others as a useful resource on agent-based financial market design as well." (Blake LeBaron, Journal of Artificial Societies and Social Simulation, Vol. 12 (2), March, 2009)
Advancing Social Simulation: The First World Congress
Agent-based modeling and social simulation have emerged as both developments of and challenges to the social sciences. The developments include agent-based computational economics and investigations of theoretical sociological concepts using formal simulation techniques. Among the challenges are the development of qualitative modeling techniques, implementation of agent-based models to investigate phenomena for which conventional economic, social, and organizational models have no face validity, and the application of physical modeling techniques to social processes. Bringing together diverse approaches to social simulation and research agendas.
Advances in Learning Classifier Systems ; 4th International Workshop, IWLCS 2001, San Francisco, CA, USA, July 7-8, 2001. Revised Papers
The Fourth International Workshop on Learning Classifier Systems (IWLCS2001) was held July 7-8, 2001, in San Francisco, California, during the Geneticand Evolutionary Computation Conference (GECCO 2001). We have includedin this volume revised and extended versions of eleven of the papers presentedat the workshop.The volume is organized into two main parts. The first is dedicated to importanttheoretical issues of learning classifier systems research including the influenceof exploration strategy, a model of self-adaptive classifier systems, and the useof classifier systems for social simulation. The second part contains papers dis-cussing applications of learning classifier systems such as data mining, stocktrading, and power distribution networks.An appendix contains a paper presenting a formal description of ACS, a rapidlyemerging learning classifier system model.
Advances in artificial life ; 8th European Conference, ECAL 2005 , Canterbury, UK, September 5-9, 2005, Proceedings
The Artificial Life term appeared more than 20 years ago . Since then the area has developed dramatically, many researchersjoining enthusiastically and research groups sprouting everywhere.a conceptual track, where papers were judged on criteria like importance and/or novelty of the concepts proposed rather than the experimental / theoretical results, has been introduced this year. A conference on a theme as broad as Artificial Life is bound to be very di-verse, but a few tendencies emerged. First, fields like ‘Robotics and Autonomous Agents’ or ‘Evolutionary Computation’are still extremely active and keep onbringing a wealth of results to the A-Life community. Even there, however, new tendencies appear, like collective robotics, and more specifically self-assembling robotics, which represent now a large subsection. Second, new areas appear.‘Morphogenesis and Development’ which used to be the subject of only a fewpapers, is now one of the largest subsections, and seems to be on the brinkof becoming a field of its own. Finally, most classical themes of A-Life re-search like ‘Artificial Chemistry’, ‘Ant-Inspired Systems’, ‘Cellular Automata’,‘Self-Replication’, ‘Social Simulations’ or ‘Bio-realist Simulations’ are still goingstrong and are well represented within this volume.
