1753 search results - page 135 / 351 » State Machines |
122
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
Partially Observable Markov Decision Processes (POMDPs) have succeeded in planning domains that require balancing actions that increase an agent's knowledge and actions that ...
150
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ICML
2006
IEEE
16 years 5 months ago
2006
IEEE
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
138
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
123
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ALIFE
2007
15 years 4 months ago
2007
Robert Rosen’s central theorem states that organisms are fundamentally different to machines, mainly because they are ‘‘closed with respect to effcient causation.’’ The p...
104
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AAAI
2010
15 years 6 months ago
2010
The results of the latest International Probabilistic Planning Competition (IPPC-2008) indicate that the presence of dead ends, states with no trajectory to the goal, makes MDPs h...