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Programming deliberation strategies in meta-APL

Leask, Sam; Logan, Brian

Authors

Sam Leask svl@cs.nott.ac.uk

Brian Logan bsl@cs.nott.ac.uk



Abstract

A key advantage of BDI-based agent programming is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages provide flexible support for expressing plans, they are typically limited to a single, hard-coded, deliberation strategy (perhaps with some parameterisation) for all task environments. In this paper, we present an alternative approach. We show how both agent programs and the agent’s deliberation strategy can be encoded in the agent programming language meta-APL. Key steps in the execution cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing BDI deliberation strategies to be programmed with ease. To illustrate the flexibility of meta-APL, we show how three typical BDI deliberation strategies can be programmed using meta-APL rules. We then show how meta-APL can used to program a novel adaptive deliberation strategy that avoids interference between intentions.

Publication Date Jan 1, 2015
Peer Reviewed Peer Reviewed
APA6 Citation Leask, S., & Logan, B. (2015). Programming deliberation strategies in meta-APL
Keywords agents, agent based programming languages, bdi, deliberation, multiagent systems
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information Published in: Chen, Q., Torroni, P., Villata, S., Hsu, J., Omicini, A. (Eds.): PRIMA 2015: Principles and Practice of Multi-Agent Systems, 18th International Conference, Bertinoro, Italy, October 26-30, 2015, Proceedings. Lecture Notes in Artificial Intelligence 9387. Cham : Springer, 2015. ISBN 9783319255231.

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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