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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/3520

Title: BDI agent architecture for a POMDP planner
Authors: Rens, G
Ferrein, A
Van der Poel, E
Keywords: Belief-Desire-Intention
BDI
Architecture
POMDP planner
POMDP model
Partially observable Markov decision process
Commonsense reasoning
Golog
9th International Symposium on Logical Formalization of Commonsense Reasoning
Issue Date: Jun-2009
Citation: Rens, G, Ferrein, A and Van der Poel, E. 2009. BDI agent architecture for a POMDP planner. 9th International Symposium on Logical Formalization of Commonsense Reasoning: Commonsense 2009, Toronto, Canada, 1-3 June, 2009. pp 6
Abstract: Traditionally, agent architectures based on the Belief-Desire-Intention (BDI) model make use of precompiled plans, or if they do generate plans, the plans do not involve stochastic actions nor probabilistic observations. Plans that do involve these kinds of actions and observations are generated by partially observable Markov decision process (POMDP) planners. In particular for POMDP planning, researchers make use of a POMDP planner which is implemented in the robot programming and plan language Golog. Golog is very suitable for integrating beliefs, as it is based on the situation calculus and researchers have drawn upon previous research on this. However, a POMDP planner on its own cannot cope well with dynamically changing environments and complicated goals. This is exactly strength of the BDI model; the model is for reasoning over goals dynamically. Therefore, in this paper, researchers propose an architecture that will lay the groundwork for architectures that combine the advantages of a POMDP planner written in the situation calculus, and the BDI model of agency. The researchers show preliminary results which can be seen as a proof of concept for integrating a POMDP into a BDI architecture
Description: 9th International Symposium on Logical Formalization of Commonsense Reasoning: Commonsense 2009, Toronto, Canada, 1-3 June 2009
URI: http://hdl.handle.net/10204/3520
ISBN: 9780980284065
Appears in Collections:High performance computing
Mobile intelligent autonomous systems
General science, engineering & technology

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