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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 language | English |
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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 |
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Dive into the research topics of 'Probabilistic Planning in AgentSpeak using the POMDP framework.'. Together they form a unique fingerprint.Projects
- 1 Finished
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R1070CSC: Providing Autonomous Capabilities for Evolving SCADA (PACES)
Liu, W. (PI), Hong, J. (CoI) & Sezer, S. (CoI)
01/08/2011 → 31/03/2016
Project: Research