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» How to Dynamically Merge Markov Decision Processes
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ALT
2006
Springer
15 years 6 months ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
JIRS
2000
121views more  JIRS 2000»
14 years 9 months ago
Entropy-Based Markov Chains for Multisensor Fusion
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...
Albert C. S. Chung, Helen C. Shen
CORR
2008
Springer
189views Education» more  CORR 2008»
14 years 9 months ago
Algorithms for Dynamic Spectrum Access with Learning for Cognitive Radio
We study the problem of dynamic spectrum sensing and access in cognitive radio systems as a partially observed Markov decision process (POMDP). A group of cognitive users cooperati...
Jayakrishnan Unnikrishnan, Venugopal V. Veeravalli
IEEEARES
2008
IEEE
15 years 4 months ago
An Ontological Approach to Secure MANET Management
Mobile Ad hoc Networks (MANETs) rely on dynamic configuration decisions to efficiently operate in a rapidly changing environment of limited resources. The ability of a MANET to ma...
Mark E. Orwat, Timothy E. Levin, Cynthia E. Irvine
AIED
2011
Springer
14 years 1 months ago
Faster Teaching by POMDP Planning
Both human and automated tutors must infer what a student knows and plan future actions to maximize learning. Though substantial research has been done on tracking and modeling stu...
Anna N. Rafferty, Emma Brunskill, Thomas L. Griffi...