On planning, prediction and knowledge transfer in fully and partially observable Markov decision processes
This dissertation addresses the problem of sequential decision making under uncertainty in large systems. The formalisms used to study this problem are fully and partially observable Markov Decision Processes (MDPs and POMDPs, respectively). The first contribution of this dissertation is a theoretic...
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| Format: | Others |
| Language: | en |
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McGill University
2011
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| Online Access: | http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=104525 |