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

This volume contains the papers selected for presentation at CEEMAS 2001. The wo- shop was the fourth in a series of international conferences devoted to autonomous agents and multi-agent systems organized in Central-Eastern Europe. Its predecessors wereCEEMAS’99andDAIMAS’97,whichtookplaceinSt. Petersburg,Russia,aswell as DIMAS’95, which took place in Cracow, Poland. Organizers of all these events made efforts to make them wide-open to participants from all over the world. This would have been impossible without some help from friendly centers in the Czech Republic, England, France, Japan, and The Netherlands. DIMAS’95 featured papers from 15 countries, while CEEMAS’99 from 18 co- tries. A total of 61 papers were submitted to CEEMAS 2001 from 17 countries. Out of these papers, 31 were selected for regular presentation, while 14 were quali ed as posters. The motto of the meeting was “Diversity is the core of multi-agent systems". This variety of subjects was clearly visible in the CEEMAS 2001 program, addressing the following major areas of multi-agent systems: – Organizations and social aspects of multi-agent systems – Agent and multi-agent system architectures, models, and formalisms – Communication languages, protocols, and negotiation – Applications of multi-agent systems – Agent and multi-agent development tools – Theoretical foundations of DistributedAI – Learning in multi-agent systems The richness of workshop subjects was ensured thanks to the CEEMAS 2001 contributing authors as well as the keynote speakers.

Adaptive Agents and Multi-Agent Systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, computer science, software engineering, and developmental biology, as well as cognitive and social science. This book surveys the state of the art in this emerging field by drawing together thoroughly selected reviewed papers from two related workshops; as well as papers by leading researchers specifically solicited for this book. The articles are organized into topical sections on - learning, cooperation, and communication - emergence and evolution in multi-agent systems - theoretical foundations of adaptive agents

This book will introduce students to intelligent agents, explain what these agents are, how they are constructed and how they can be made to co-operate effectively with one another in large-scale systems.

The quality of ecosystems is affected by the actions of different stakeholders who use them in a variety of ways. In order to understand this complex relationship between humans and nature, it is vital to understand the complexity of the interacting agents. The authors in this book attempt to do this by applying multi-agent systems to the problems of ecosystem management. The multi-agent approach to ecosystem management is a relatively new and rapidly developing field which takes a formal computational approach towards the interaction of humans with their environment. The authors highlight some of the promising new methodologies which are emerging in the field from disciplines such as computer science and computational social science. They move on to address a number of important topics including diffusion processes, common-pool resources, land use change and the participatory use of models, in an attempt to solve contemporary management issues. They clearly demonstrate the potential utility of multi-agent systems in the context of theoretical problems and practical case studies.

This book constitutes the thoroughly refereed post-proceedings of the Third International Workshop on Environments for Multiagent Systems, E4MAS 2006, held in Hakodate, Japan in May 2006 as an associated event of AAMAS 2006, the 5th International Joint Conference on Autonomous Agents and Multiagent Systems. The 15 revised papers presented were carefully reviewed and selected from the lectures given at the workshop completed by a number of invited papers of prominent researchers active in the domain. The papers are organized in topical sections on models, architecture, and design, mediated inte.

This book constitutes revised selected papers from the 9th International Workshop on Engineering Multi-Agent Systems, EMAS 2021, which was held during May 3-4, 2021. The conference was initially planned to take place in London, UK, but changed to an online event due to the COVID-19 pandemic. The 20 full papers and 1 short paper included in this volume were carefully reviewed and selected from a total of 27 submissions. The contributions deal with agent-oriented software engineering, programming multi-agent systems, declarative agent languages and technologies, artificial intelligence, and machine learning.