Agent-oriented probabilistic logic programming

Authors:
Jie Wang;Shi-Er Ju;Chun-Nian Liu
Affiliations:
Key Laboratory of Multimedia and Intelligent Software, Beijing University of Technology, Beijing, P.R. China;Institute of Logic and Cognition, Zhongshan University, Guangzhou, P.R. China;Key Laboratory of Multimedia and Intelligent Software, Beijing University of Technology, Beijing, P.R. China
Venue:
Journal of Computer Science and Technology - Special section on China AVS standard
Year:
2006

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Abstract

Currently, agent-based computing is an active research area, and great efforts have been made towards the agent-oriented programming both from a theoretical and practical view. However, most of them assume that there is no uncertainty in agents' mental state and their environment. In other words, under this assumption agent developers are just allowed to specify how his agent acts when the agent is 100% sure about what is true/false. In this paper, this unrealistic assumption is removed and a new agent-oriented probabilistic logic programming language is proposed, which can deal with uncertain information about the world. The programming language is based on a combination of features of probabilistic logic programming and imperative programming.