Distributed Artificial Intelligence (DAI) is a vibrant sub-field of Artificial Intelligence concerned with coordinating the knowledge and actions of multiple interacting agents. Although DAI has the potential to overcome many of the problems currently associated with constructing software systems which are large, complex and knowledge rich, there have, as yet, been relatively few attempts to apply it to real world applications. To help pave the way for such future developments, this book recounts the insights gained and the breakthroughs made, whilst building multiple agent systems in the domains of electricity transportation management and control of a particle accelerator. These experiences cover the complete development lifecycle of multi-agent systems for industrial applications: ranging from the initial design, through the implementation, to the testing and evaluation phases. The book's other main features are that it: provides a thorough and up-to-date explanation of the foundation concepts of DAI, describes a new paradigm for building multi-agent systems which uses the concept of reusable cooperation knowledge and develops a new model of cooperation based on the notion of joint intentions.
Initial experiences of building industrial multi-agent systems; representing co-ordination in multi-agent systems; Grate*: a co-operation knowledge level multi-agent system; conclusion and future directions.