These conference proceedings describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to co-operate or compete. A comprehensive introductory survey on the areas involved is included.

This work is based on the workshop on adaptation and learning in multi-agent systems, held in conjunction with the International Joint Conference on Artificial Intelligence, IJCAI'95, in Montreal, Canada in August 1995. The papers describe and analyze, both experimentally and theoretically, new learning and adaption approaches for situations in which several agents have to co-operate or compete. Also included, and aimed at the novice reader, are a comprehensive introductory survey on the areas with 154 references listed and a subject index.