Recent Advances in Reinforcement Learning

Table of Contents

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   Book Overview
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   Chapter 1 Invited Talk: UCRL and Autonomous Exploration
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   Chapter 2 Invited Talk: Increasing Representational Power and Scaling Inference in Reinforcement Learning
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   Chapter 3 Invited Talk: PRISM – Practical RL: Representation, Interaction, Synthesis, and Mortality
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   Chapter 4 Invited Talk: Towards Robust Reinforcement Learning Algorithms
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   Chapter 5 Automatic Discovery of Ranking Formulas for Playing with Multi-armed Bandits
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   Chapter 6 Goal-Directed Online Learning of Predictive Models
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   Chapter 7 Gradient Based Algorithms with Loss Functions and Kernels for Improved On-Policy Control
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   Chapter 8 Active Learning of MDP Models
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    Chapter 9 Handling Ambiguous Effects in Action Learning
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    Chapter 10 Feature Reinforcement Learning in Practice
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    Chapter 11 Reinforcement Learning with a Bilinear Q Function
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    Chapter 12 ℓ 1 -Penalized Projected Bellman Residual
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    Chapter 13 Regularized Least Squares Temporal Difference Learning with Nested ℓ 2 and ℓ 1 Penalization
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    Chapter 14 Recursive Least-Squares Learning with Eligibility Traces
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    Chapter 15 Value Function Approximation through Sparse Bayesian Modeling
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    Chapter 16 Automatic Construction of Temporally Extended Actions for MDPs Using Bisimulation Metrics
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    Chapter 17 Unified Inter and Intra Options Learning Using Policy Gradient Methods
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    Chapter 18 Options with Exceptions
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    Chapter 19 Robust Bayesian Reinforcement Learning through Tight Lower Bounds
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    Chapter 20 Optimized Look-ahead Tree Search Policies
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    Chapter 21 A Framework for Computing Bounds for the Return of a Policy
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    Chapter 22 Transferring Evolved Reservoir Features in Reinforcement Learning Tasks
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    Chapter 23 Transfer Learning via Multiple Inter-task Mappings
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    Chapter 24 Multi-Task Reinforcement Learning: Shaping and Feature Selection
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    Chapter 25 Transfer Learning in Multi-Agent Reinforcement Learning Domains
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    Chapter 26 An Extension of a Hierarchical Reinforcement Learning Algorithm for Multiagent Settings
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    Chapter 27 Bayesian Multitask Inverse Reinforcement Learning
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    Chapter 28 Batch, Off-Policy and Model-Free Apprenticeship Learning
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    Chapter 29 Introduction of Fixed Mode States into Online Profit Sharing and Its Application to Waist Trajectory Generation of Biped Robot
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    Chapter 30 MapReduce for Parallel Reinforcement Learning
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    Chapter 31 Compound Reinforcement Learning: Theory and an Application to Finance
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    Chapter 32 Proposal and Evaluation of the Active Course Classification Support System with Exploitation-Oriented Learning