Recent Advances in Reinforcement Learning 8th European Workshop, EWRL 2008, Villeneuve d’Ascq, France, June 30-July 3, 2008, Revised and Selected Papers /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Girgin, Sertan (Επιμελητής έκδοσης), Loth, Manuel (Επιμελητής έκδοσης), Munos, Rémi (Επιμελητής έκδοσης), Preux, Philippe (Επιμελητής έκδοσης), Ryabko, Daniil (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Lecture Notes in Computer Science, 5323
• Θέματα: Computer science.; Computer programming.; Computers.; Database management.; Artificial intelligence.; Computer Science.; Artificial Intelligence (incl. Robotics).; Programming Techniques.; Theory of Computation.; Computation by Abstract Devices.; Information Systems Applications (incl. Internet).; Database Management.

 This book constitutes revised and selected papers of the 8th European Workshop on Reinforcement Learning, EWRL 2008, which took place in Villeneuve d'Ascq, France, during June 30 - July 3, 2008. The 21 papers presented were carefully reviewed and selected from 61 submissions. They are dedicated to the field of and current researches in reinforcement learning. 

 Lazy Planning under Uncertainty by Optimizing Decisions on an Ensemble of Incomplete Disturbance Trees -- Exploiting Additive Structure in Factored MDPs for Reinforcement Learning -- Algorithms and Bounds for Rollout Sampling Approximate Policy Iteration -- Efficient Reinforcement Learning in Parameterized Models: Discrete Parameter Case -- Regularized Fitted Q-Iteration: Application to Planning -- A Near Optimal Policy for Channel Allocation in Cognitive Radio -- Evaluation of Batch-Mode Reinforcement Learning Methods for Solving DEC-MDPs with Changing Action Sets -- Bayesian Reward Filtering -- Basis Expansion in Natural Actor Critic Methods -- Reinforcement Learning with the Use of Costly Features -- Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem -- Optimistic Planning of Deterministic Systems -- Policy Iteration for Learning an Exercise Policy for American Options -- Tile Coding Based on Hyperplane Tiles -- Use of Reinforcement Learning in Two Real Applications -- Applications of Reinforcement Learning to Structured Prediction -- Policy Learning – A Unified Perspective with Applications in Robotics -- Probabilistic Inference for Fast Learning in Control -- United We Stand: Population Based Methods for Solving Unknown POMDPs -- New Error Bounds for Approximations from Projected Linear Equations -- Markov Decision Processes with Arbitrary Reward Processes.