GENERAL ENQUIRIES: Tel: + 27 12 841 2911 | Email: callcentre@csir.co.za

Show simple item record

dc.contributor.author Rens, GB
dc.contributor.author Meyer, TA
dc.date.accessioned 2016-06-27T08:39:10Z
dc.date.available 2016-06-27T08:39:10Z
dc.date.issued 2015-01
dc.identifier.citation Rens, GB and Meyer, TA. 2015. A Hybrid POMDP-BDI Agent Architecture with Online Stochastic Planning and Desires with Changing Intensity Levels. In 7th Proceedings of the International Conference on Agents and Artificial Intelligence (ICAART), 10 - 12 January 2015, Lisbon, Portugal en_US
dc.identifier.isbn 978-3-319-27946-6
dc.identifier.uri http://link.springer.com/chapter/10.1007%2F978-3-319-27947-3_1
dc.identifier.uri http://hdl.handle.net/10204/8579
dc.description ICAART 2015, 7th International Conference on Agents and Artificial Intelligence, Lisbon, Portugal, 10-12 January 2015. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website en_US
dc.description.abstract The authors propose an agent architecture which combines Partially observable Markov decision processes (POMDPs) and the belief-desire-intention (BDI) framework have several complementary strengths. The authors propose an agent architecture, which combines these two powerful approaches to capitalize on their strengths. Their architecture introduces the notion of intensity of the desire for a goal’s achievement. We also define an update rule for goals’ desire levels. When to select a new goal to focus on is also defined. To verify that the proposed architecture works, experiments were run with an agent based on the architecture, in a domain where multiple goals must continually be achieved. The results show that (i) while the agent is pursuing goals, it can concurrently perform rewarding actions not directly related to its goals, (ii) the trade-off between goals and preferences can be set effectively and (iii) goals and preferences can be satisfied even while dealing with stochastic actions and perceptions. They believe that the proposed architecture furthers the theory of high-level autonomous agent reasoning. en_US
dc.language.iso en en_US
dc.publisher Springerlink en_US
dc.relation.ispartofseries Workflow;15636
dc.subject Partially observable Markov decision processes en_US
dc.subject POMDP en_US
dc.subject Belief-desire-intention en_US
dc.subject BDI en_US
dc.subject Preference en_US
dc.title Hybrid POMDP-BDI Agent Architecture with Online Stochastic Planning and Desires with Changing Intensity Levels en_US
dc.type Presentation en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ResearchSpace


Advanced Search

Browse

My Account