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← Reinforcement Learning
Reinforcement Learning ›

Methods

6,493 papers (10 classified directly here)

Subtopics

Deep RL (3,886) Policy Learning (2,076) Multi-Agent Systems (1,019) Offline RL (726) Meta-Learning (25) Model-Based RL (12)

Papers per year

2
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34
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530
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Papers (including subtopics)

Non-delusional Q-learning and value-iteration NIPS 2018
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning NIPS 2018
Learning Others' Intentional Models in Multi-Agent Settings Using Interactive POMDPs NIPS 2018
Balanced Policy Evaluation and Learning NIPS 2018
Policy Optimization via Importance Sampling NIPS 2018
Transfer of Deep Reactive Policies for MDP Planning NIPS 2018
Simple random search of static linear policies is competitive for reinforcement learning NIPS 2018
Evolved Policy Gradients NIPS 2018
Iterative Value-Aware Model Learning NIPS 2018
Policy-Conditioned Uncertainty Sets for Robust Markov Decision Processes NIPS 2018
Visual Reinforcement Learning with Imagined Goals NIPS 2018
Inequity aversion improves cooperation in intertemporal social dilemmas NIPS 2018
Distributed Multitask Reinforcement Learning with Quadratic Convergence NIPS 2018
A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents NIPS 2018
Evolution-Guided Policy Gradient in Reinforcement Learning NIPS 2018
Online Robust Policy Learning in the Presence of Unknown Adversaries NIPS 2018
Reward learning from human preferences and demonstrations in Atari NIPS 2018
Post: Device Placement with Cross-Entropy Minimization and Proximal Policy Optimization NIPS 2018
A Bayesian Approach to Generative Adversarial Imitation Learning NIPS 2018
Credit Assignment For Collective Multiagent RL With Global Rewards NIPS 2018
Learning Beam Search Policies via Imitation Learning NIPS 2018
Unsupervised Video Object Segmentation for Deep Reinforcement Learning NIPS 2018
Representation Balancing MDPs for Off-policy Policy Evaluation NIPS 2018
Reinforcement Learning for Solving the Vehicle Routing Problem NIPS 2018
Diversity-Driven Exploration Strategy for Deep Reinforcement Learning NIPS 2018