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A Framework for Comparing Agent Architectures

By Aaron Sloman and Matthias Scheutz


Research on algorithms and representations once dominated AI. Recently the importance of architectures has been acknowledged, but researchers have different objectives, presuppositions and conceptual frameworks, and this, can lead to confused terminology, argumentation at cross purposes, re-invention of wheels and fragmentation of the research. We propose a methodological framework: develop a representation of a general class of architectures within which different architectures can be compared and contrasted. This should facilitate communication and integration across sub-fields of and approaches to AI, as well providing a framework for evaluating alternative architectures. As a first-draft example we present the CogAff architecture schema, and show how it provides a draft framework. But there is much still to be done

Year: 2002
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