Learning and Adaption in Multi-Agent Systems ; 1st International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers
Contains selected and revised papers of the International Workshop on Lea- ing and Adaptation in Multi-Agent Systems (LAMAS 2005), held at the AAMAS 2005 Conference in Utrecht, The Netherlands, July 26. An important aspect in multi-agent systems (MASs) is that the environment evolves over time, not only due to external environmental changes but also due to agent int- actions. For this reason it is important that an agent can learn, based on experience, and adapt its knowledge to make rational decisions and act in this changing environment autonomously. Machine learning techniques for single-agent frameworks are well established. Agents operate in uncertain environments and must be able to learn and act - tonomously. This task is, however, more complex when the agent interacts with other agents that have potentially different capabilities and goals. The single-agent case is structurally different from the multi-agent case due to the added dimension of dynamic interactions between the adaptive agents. Multi-agent learning, i.e., the ability of the agents to learn how to cooperate and compete, becomes crucial in many domains. Autonomous agents and multi-agent systems (AAMAS) is an emerging multi-disciplinary area encompassing computer science, software engineering, biology, as well as cognitive and social sciences. A t- oretical framework, in which rationality of learning and interacting agents can be - derstood, is still under development in MASs, although there have been promising ?
Agent Computing and Multi-Agent Systems ; 9th Pacific Rim International Workshop on Multi-Agents, PRIMA 2006, Guilin, China, August 7-8, 2006, Proceedings
PRIMA is a series of workshops on agent computing and multi-agent systems, integrating the activities in Asia and Pacific Rim countries. Agent computing and multi-agent systems are computational systems in which several autonomous or se- autonomous agents interact with each other or work together to perform some set of tasks or satisfy some set of goals. These systems may involve computational agents that are homogeneous or heterogeneous, they may involve activities on the part of agents having common or distinct goals, and they may involve participation on the part of humans and intelligent agents. The aim of PRIMA 2006 was to bring together Asian and Pacific Rim researchers and developers from academia and industry to report on the latest technical advances or domain applications and to discuss and explore scientific and practical problems as raised by the participants. PRIMA 2006 received 203 submitted papers.
Advances in web-based learning - ICWL 2005 ; 4th international conference, Hong Kong, China, July 31 - August 3, 2005, proceedings
With the rapid development of Web-based learning, a new set of learning - vironments including virtual classrooms, virtual laboratories and virtual universities are being developed. These new learning environments, however, also introduce new problems that need to be addressed. On the technical side, there is a need for the deployment of effective technologies on Web-based education. On the learning side, the cyber mode of learning is very different from tra- tional classroom-based learning. On the management side, the establishment of a cyber university imposes very different requirements for the set up. ICWL 2005, the 4th International Conference on Web-Based Learning, was held in Hong Kong, China from July 31 to August 3, 2005, as a continued - tempt to address many of the above-mentioned issues. Following the great success of ICWL
Advances in web based learning - ICWL 2007 ; 6th International conference Edinburgh, UK, August 15-17, 2007 Revised Papers
This book contributes the thoroughly refereed post-conference proceedings of the 6th International Conference on Web-Based Learning, ICWL 2007, held in Edinburgh, UK, in August 2007.
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.
Adaptive agents and multi-agent systems III : Adaptation and multi-Agent learning ; 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers
This book contains selected and revised papers of the European Symposium on Adaptive and Learning Agents and Multi-Agent Systems (ALAMAS).
Adaptive agents and multi-agent systems II : Adaptation and multi-agent learning
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.






