Belief Generalization for Intelligent Agents
One of the important characteristics for intelligent agents is to be able to assess their environments in order to generate correct beliefs to make right decisions. It is always difficult to do so because many factors including uncertain information, knowledge and bounded time will affect intelligent agents to perceive their environments. In this paper, we propose a procedure descriptive framework rather than a logical model to describe how agents automatically form their beliefs. The process of belief updating in this framework remains to be constantly changing, until the point of decision making is reached. Using this framework, a subject agent can smoothly fuse its knowledge and possible information from the current environment in order to obtain correct beliefs. We also present a solution for conflict resolution between agents in this framework.
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|Item Type:||Journal Article|
|Keywords:||Intelligent agents, belief, uncertainty|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Neural Evolutionary and Fuzzy Computation (080108)|
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Education
Past > QUT Faculties & Divisions > Faculty of Science and Technology
|Copyright Owner:||Copyright 2003 Grace Publications|
|Deposited On:||28 Sep 2005|
|Last Modified:||29 Feb 2012 12:59|
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