Observation-based Model for BDI-Agents

Su, Kaile, Sattar, Abdul, Wang, Kewen, Luo, Xiangyu, Governatori, Guido and Padmanabhan, Vineet (2005). Observation-based Model for BDI-Agents. In: Proceedings of: 20th National Conference on Artificial Intelligence (AAAI). 20th National Conference on Artificial Intelligence (AAAI), Pittsburgh, USA, (). 9-13 July, 2005.

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Author Su, Kaile
Sattar, Abdul
Wang, Kewen
Luo, Xiangyu
Governatori, Guido
Padmanabhan, Vineet
Title of paper Observation-based Model for BDI-Agents
Conference name 20th National Conference on Artificial Intelligence (AAAI)
Conference location Pittsburgh, USA
Conference dates 9-13 July, 2005
Proceedings title Proceedings of: 20th National Conference on Artificial Intelligence (AAAI)
Place of Publication Menlo Park, California, USA
Publisher American Association for Artificial Intelligence
Publication Year 2005
Sub-type Fully published paper
Total pages 6
Language eng
Abstract/Summary We present a new computational model of BDI-agents, called the observation-based BDI-model. The key point of this BDI-model is to express agents' beliefs, desires and intentions as a set of runs (computing paths), which is exactly a system in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our BDI-model is computationally grounded in that we are able to associate the BDI-agent model with a computer program, and formulas, involving agents' beliefs, desires (goals) and intentions, can be understood as properties of program computations. We present a sound and complete proof system with respect to our BDI-model and explore how symbolic model checking techniques can be applied to model checking BDI-agents. In order to make our BDI-model more flexible and practically realistic, we generalize it so that agents can have multiple sources of beliefs, goals and intentions.
Subjects 280403 Logics and Meanings of Programs
280200 Artificial Intelligence and Signal and Image Processing
Keyword multi modal logics
interpreted systems
model checking
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Copyright (c) 2005 American Association for Artificial Intelligence (www.aaai.org). All rights reserved.

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Created: Mon, 23 May 2005, 10:00:00 EST by Guido Governatori on behalf of Scholarly Communication and Digitisation Service