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 STYLE
Bauters, K., McAreavey, K., Hong, J., Chen, Y., Liu, W., Godo, L., & Sierra, C. (2016). Probabilistic planning in agentspeak using the POMDP framework. In Smart Innovation, Systems and Technologies (Vol. 46, pp. 19–37). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-26860-6_2
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