conftrace_

value iteration

162 papers

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Also known as

VI

Co-occurring keywords

reinforcement learning (4352) markov decision process (790) regret bound (1926) offline reinforcement learning (492) function approximation (319) dynamic programming (274) policy iteration (99) sample complexity (1169) model-based reinforcement learning (415) policy learning (702)

Papers

Tightening Exploration in Upper Confidence Reinforcement Learning ICML 2020
Reinforcement Learning with Dynamic Boltzmann Softmax Updates IJCAI 2020
Provable Self-Play Algorithms for Competitive Reinforcement Learning ICML 2020
Transfer Value Iteration Networks AAAI 2020
Adaptive Discretization for Model-Based Reinforcement Learning NIPS 2020
The Value Equivalence Principle for Model-Based Reinforcement Learning NIPS 2020
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes NIPS 2020
Off-Policy Interval Estimation with Lipschitz Value Iteration NIPS 2020
Provably Efficient Reward-Agnostic Navigation with Linear Value Iteration NIPS 2020
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning NIPS 2020
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks AAAI 2020
AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample Complexity AISTATS 2020
Momentum in Reinforcement Learning AISTATS 2020
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm NIPS 2019
A Theory of Regularized Markov Decision Processes ICML 2019
Explicit Planning for Efficient Exploration in Reinforcement Learning NIPS 2019
Approximate Relative Value Learning for Average-reward Continuous State MDPs UAI 2019
Limiting Extrapolation in Linear Approximate Value Iteration NIPS 2019
Finding Options that Minimize Planning Time ICML 2019
Advantage Amplification in Slowly Evolving Latent-State Environments IJCAI 2019
Planning in entropy-regularized Markov decision processes and games NIPS 2019
How to Combine Tree-Search Methods in Reinforcement Learning AAAI 2019
Learning to Plan with Logical Automata RSS 2019
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning AISTATS 2019
Iterative Value-Aware Model Learning NIPS 2018