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. The 15 revised papers in this volume are organized in topical sections on models, architecture, and design, mediated interaction and stigmery, governing environment, and applications.

This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Environments for Multiagent Systems, E4MAS 2005, held in July 2005. The 16 revised papers presented were carefully reviewed and selected from the lectures given at the workshop. The papers are organized in topical sections on models, architecture, and design, mediated coordination, as well as applications.

The modern ?eld of multiagent systems has developed from two main lines of earlier research. Its practitioners generally regard it as a form of arti?cial intelligence (AI). Some of its earliest work was reported in a series of workshops in the US dating from1980, revealinglyentitled, DistributedArti?cialIntelligence, andpioneers often quoted a statement attributed to Nils Nilsson that all AI is distributed. The locus of classical AI was what happens in the head of a single agent, and much MAS research re?ects this heritage with its emphasis on detailed modeling of the mental state and processes of individual agents. From this perspective, intelligenceisultimatelythepurviewofasinglemind, thoughitcanbeampli?ed by appropriate interactions with other minds. These interactions are typically mediated by structured protocols of various sorts, modeled on human conver- tional behavior. But the modern ?eld of MAS was not born of a single parent. A few - searchershavepersistentlyadvocatedideasfromthe?eldofarti?ciallife(ALife). These scientists were impressed by the complex adaptive behaviors of commu- ties of animals (often extremely simple animals, such as insects or even micro- ganisms). The computational models on which they drew were often created by biologists who used them not to solve practical engineering problems but to test their hypotheses about the mechanisms used by natural systems. In the ar- ?cial life model, intelligence need not reside in a single agent, but emerges at the level of the community from the nonlinear interactions among agents. - cause the individual agents are often subcognitive, their interactions cannot be modeled by protocols that presume linguistic competence."

This book constitutes the thoroughly refereed post-workshop proceedings of the 4th International Workshop on Environments for Multiagent Systems, E4MAS 2014 - 10 years later, held in Paris, France, in May 2014 as an associated event of AAMAS 2014, the 13th International Conference on Autonomous Agents and Multiagent Systems. The 6 revised full papers presented together with 1 roadmap paper and 7 invited papers were carefully reviewed and selected from 14 initial submissions. The papers are organized in topical sections on connecting agents, environments, and humans; environments for complex and stigmergic systems; virtual and simulated environments; and open agent environments and interoperability.