Moodley, DRens, Gavin2017-08-222017-08-222016-12Rens, G. and Moodley, D. 2016. A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching. Cognitive Systems Research, vol. 43:1-20. doi.org/10.1016/j.cogsys.2016.12.0021389-0417doi.org/10.1016/j.cogsys.2016.12.002http://www.sciencedirect.com/science/article/pii/S1389041716300870http://hdl.handle.net/10204/9452Copyright: 2016 Elsevier. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, kindly consult the publisher's website.This article presents an agent architecture for controlling an autonomous agent in stochastic, noisy environments. The architecture combines the partially observable Markov decision process (POMDP) model with the belief-desire-intention (BDI) framework. The Hybrid POMDP-BDI agent architecture takes the best features from the two approaches, that is, the online generation of reward-maximizing courses of action from POMDP theory, and sophisticated multiple goal management from BDI theory. We introduce the advances made since the introduction of the basic architecture, including (i) the ability to pursue and manage multiple goals simultaneously and (ii) a plan library for storing pre-written plans and for storing recently generated plans for future reuse. A version of the architecture is implemented and is evaluated in a simulated environment. The results of the experiments show that the improved hybrid architecture outperforms the standard POMDP architecture and the previous basic hybrid architecture for both processing speed and effectiveness of the agent in reaching its goals.enPartially observable Markov decision processPOMDPBelief-desire-intentionBDIArticleMoodley, D., & Rens, G. (2016). A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching. http://hdl.handle.net/10204/9452Moodley, D, and Gavin Rens "A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching." (2016) http://hdl.handle.net/10204/9452Moodley D, Rens G. A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching. 2016; http://hdl.handle.net/10204/9452.TY - Article AU - Moodley, D AU - Rens, Gavin AB - This article presents an agent architecture for controlling an autonomous agent in stochastic, noisy environments. The architecture combines the partially observable Markov decision process (POMDP) model with the belief-desire-intention (BDI) framework. The Hybrid POMDP-BDI agent architecture takes the best features from the two approaches, that is, the online generation of reward-maximizing courses of action from POMDP theory, and sophisticated multiple goal management from BDI theory. We introduce the advances made since the introduction of the basic architecture, including (i) the ability to pursue and manage multiple goals simultaneously and (ii) a plan library for storing pre-written plans and for storing recently generated plans for future reuse. A version of the architecture is implemented and is evaluated in a simulated environment. The results of the experiments show that the improved hybrid architecture outperforms the standard POMDP architecture and the previous basic hybrid architecture for both processing speed and effectiveness of the agent in reaching its goals. DA - 2016-12 DB - ResearchSpace DP - CSIR KW - Partially observable Markov decision process KW - POMDP KW - Belief-desire-intention KW - BDI LK - https://researchspace.csir.co.za PY - 2016 SM - 1389-0417 T1 - A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching TI - A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching UR - http://hdl.handle.net/10204/9452 ER -