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FLAIRS
2004
15 years 4 months ago
State Space Reduction For Hierarchical Reinforcement Learning
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
Mehran Asadi, Manfred Huber
CVPR
2011
IEEE
14 years 11 months ago
Learning Non-Local Range Markov Random Field for Image Restoration
In this paper, we design a novel MRF framework which is called Non-Local Range Markov Random Field (NLRMRF). The local spatial range of clique in traditional MRF is extended to th...
Sun Jian, Marshall Tappen
ATAL
2007
Springer
15 years 9 months ago
Theoretical advantages of lenient Q-learners: an evolutionary game theoretic perspective
This paper presents the dynamics of multiple reinforcement learning agents from an Evolutionary Game Theoretic (EGT) perspective. We provide a Replicator Dynamics model for tradit...
Liviu Panait, Karl Tuyls
ECAI
2006
Springer
15 years 6 months ago
A Unified Model for Multilabel Classification and Ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate...
Klaus Brinker, Johannes Fürnkranz, Eyke H&uum...
DAC
2005
ACM
16 years 4 months ago
Structural search for RTL with predicate learning
We present an efficient search strategy for satisfiability checking on circuits represented at the register-transfer-level (RTL). We use the RTL circuit structure by extending con...
Ganapathy Parthasarathy, Madhu K. Iyer, Kwang-Ting...