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» Learning Partially Observable Deterministic Action Models
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GPEM
2008
128views more  GPEM 2008»
13 years 7 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
TSP
2010
13 years 2 months ago
Testing stationarity with surrogates: a time-frequency approach
An operational framework is developed for testing stationarity relatively to an observation scale, in both stochastic and deterministic contexts. The proposed method is based on a ...
Pierre Borgnat, Patrick Flandrin, Paul Honeine, C&...
AI
2011
Springer
13 years 2 months ago
First-order logical filtering
Logical filtering is the process of updating a belief state (set of possible world states) after a sequence of executed actions and perceived observations. In general, it is intr...
Afsaneh Shirazi, Eyal Amir
CORR
2011
Springer
194views Education» more  CORR 2011»
12 years 11 months ago
Accelerating Reinforcement Learning through Implicit Imitation
Imitation can be viewed as a means of enhancing learning in multiagent environments. It augments an agent’s ability to learn useful behaviors by making intelligent use of the kn...
Craig Boutilier, Bob Price
AAAI
2007
13 years 10 months ago
Purely Epistemic Markov Decision Processes
Planning under uncertainty involves two distinct sources of uncertainty: uncertainty about the effects of actions and uncertainty about the current state of the world. The most wi...
Régis Sabbadin, Jérôme Lang, N...