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.
|Title of host publication||Combinations of Intelligent Methods and Applications (An invited, extended version of CIMA'14 paper)|
|Editors||I Hatzilygeroudis, V. Palade, J. Prentzas|
|Number of pages||19|
|Publication status||Accepted - 2015|
Bauters, K., McAreavey, K., Hong, J., Chen, Y., Liu, W., Godo, L., & Sierra, C. (Accepted/In press). Probabilistic Planning in AgentSpeak using the POMDP framework. In I. Hatzilygeroudis, V. Palade, & J. Prentzas (Eds.), Combinations of Intelligent Methods and Applications (An invited, extended version of CIMA'14 paper) http://ictai2014.cs.ucy.ac.cy/index.php?p=Program