A belief-desire-intention architechture with a logic-based planner for agents in stochastic domains
This dissertation investigates high-level decision making for agents that are both goal and utility driven. We develop a partially observable Markov decision process (POMDP) planner which is an extension of an agent programming language called DTGolog, itself an extension of the Golog language. G...
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| Format: | Others |
| Language: | en |
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2010
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| Online Access: | http://hdl.handle.net/10500/3517 |
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