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UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
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I report about a particular approach to heterogenous agent systems, IMPACT, which is strongly related to computational logic. The underlying methods and techniques stem from both non-monotonic reasoning and logic programming. I present three recent extensions to illustrate the generality and usefulness of the approach: (1) incorporating planning, (2) uncertain (probabilistic) reasoning, and (3) reducing the load of serving multiple requests. While (1) illustrates how easy it is to incorporate hierachical task networks into IMPACT, (2) makes heavily use of annotated logic programming and (3) is strongly related to classical first-order reasoning. This paper is a high-level description of (1)-(3), More detailed expositions can be found in [1,2,3,4] from which most parts of this paper are taken.