Abstract
There has been considerable progress in both the theory and practice of agent programming since Georgeff and Rao's seminal work on the belief-desire-intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are confined to a small number of niche areas and adoption of agent programming languages in mainstream software development remains limited. This state of affairs is widely acknowledged within the community and a number of reasons and remedies have been proposed. In this paper, I present an analysis of why agent programming has failed to make an impact that is rooted in the class of programming problems agent programming sets out to solve, namely the realisation of flexible intelligent behaviour in dynamic and unpredictable environments. Based on this analysis, I outline some suggestions for the future direction of agent programming and some principles that I believe any successful future direction must follow.
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