Probabilistic planning in agentspeak using the POMDP framework

Godo, Llu�s; Bauters, Kim; McAreavey, Kevin; Hong, Jun; Chen, Yingke; Liu, Weiru; Godo, Llu\'\is; Sierra, Carles

Abstract

© Springer International Publishing Switzerland 2016. AgentSpeak is a logic-based programming language, based on the Belief- Desire-Intention 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 thiswork, 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 faced with uncertainty.

Citation

Godo, L., Bauters, K., McAreavey, K., Hong, J., Chen, Y., Liu, W., …Sierra, C. (2016). Probabilistic planning in agentspeak using the POMDP framework. https://doi.org/10.1007/978-3-319-26860-6_2

• Journal Article Type: Conference Paper
• Publication Date: Jan 1, 2016
• Deposit Date: Feb 17, 2017
• Journal: Smart Innovation, Systems and Technologies
• Electronic ISSN: 2190-3026
• Peer Reviewed: Peer Reviewed
• Volume: 46
• Pages: 19-37
• Book Title: Combinations of Intelligent Methods and Applications
• ISBN: 9783319268583
• DOI: https://doi.org/10.1007/978-3-319-26860-6_2
• Keywords: probabilistic planning, AgentSpeak, POMDP
• Public URL: https://uwe-repository.worktribe.com/output/914774
• Publisher URL: http://rd.springer.com/chapter/10.1007/978-3-319-26860-6_2