Methods

Effective Diversity in Population Based Reinforcement Learning NeurIPS 2020 Efficient Deep Reinforcement Learning via Adaptive Policy Transfer IJCAI 2020 Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization NeurIPS 2020 Efficiently Solving MDPs with Stochastic Mirror Descent ICML 2020 Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning NeurIPS 2020 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation ICML 2020 Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning AISTATS 2020 Efficient Policy Learning from Surrogate-Loss Classification Reductions ICML 2020 Elaborating on Learned Demonstrations with Temporal Logic Specifications RSS 2020 Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design NeurIPS 2020 Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning RSS 2020 Emergent Reciprocity and Team Formation from Randomized Uncertain Social Preferences NeurIPS 2020 Emergent Tool Use From Multi-Agent Autocurricula ICLR 2020 Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions ICML 2020 Episodic Reinforcement Learning with Associative Memory ICLR 2020 Ergodic Specifications for Flexible Swarm Control: From User Commands to Persistent Adaptation RSS 2020 ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract) AAAI 2020 Error Bounds of Imitating Policies and Environments NeurIPS 2020 ES-MAML: Simple Hessian-Free Meta Learning ICLR 2020 Estimating Q(s,s’) with Deep Deterministic Dynamics Gradients ICML 2020 Evaluating the Performance of Reinforcement Learning Algorithms ICML 2020 Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning ICLR 2020 Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination ICML 2020 ExpanRL: Hierarchical Reinforcement Learning for Course Concept Expansion in MOOCs AACL 2020 Expected Policy Gradients for Reinforcement Learning JMLR 2020