AgentSpeak+: AgentSpeak with probabilistic planning

Yingke Chen, Kim Bauters, Weiru Liu, Jun Hong, Kevin McAreavey, Lluis Godo, Carles Sierra

Research output: Contribution to conferenceOther Conference Contributionpeer-review

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Abstract

AgentSpeak is a logic-based programming language, based on the Belief-Desire-Intention (BDI) paradigm, suitable for building complex agent-based systems. To limit the computational complexity, agents in AgentSpeak rely on a plan library to reduce the planning problem to the much simpler problem of plan selection. However, such a plan library is often inadequate when an agent is situated in an uncertain environment. In this paper, we propose the AgentSpeak+ framework, which extends AgentSpeak with a mechanism for probabilistic planning. The beliefs of an AgentSpeak+ agent are represented using epistemic states to allow an agent to reason about its uncertain observations and the uncertain effects of its actions. Each epistemic state consists of a POMDP, used to encode the agent’s knowledge of the environment, and its associated probability distribution (or belief state). In addition, the POMDP is used to select the optimal actions for achieving a given goal, even when facing uncertainty.
Original languageEnglish
Pages15-20
Number of pages6
Publication statusPublished - 1 Nov 2014
Event26th International Conference on Tools with Artificial Intelligence: 4th International Workshop on Combinations of Intelligent Methods and Applications -
Duration: 10 Nov 2014 → …

Conference

Conference26th International Conference on Tools with Artificial Intelligence
Abbreviated titleCIMA 14
Period10/11/14 → …

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