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David Silver

51 papers · 2008–2022 · 8 conferences · across top CS/AI conferences

Achievements

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🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (22) 🌍 Conference Polyglot (8)

🗺️ Taxonomy Completionist (22) 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (14) 🏠 Conference Loyalist (23) 🌟 Keyword Trendsetter Combo (6) 🤝 Dynamic Duo (15) 👑 Triple Crown 🌱 Topic Pioneer 🧬 Topic Evolution 🏆 Keyword Champion (3) 🏆 Grand Slam 🔬 Deep Specialist (26) 🗃️ Keyword Collector (85) 📈 Trend Setter 🔥 Unstoppable (15) 🚀 Conference Pioneer ⚡ Prolific Year (7) 💎 Century Club (51) ❓ The Questioner

Conferences

NIPS (23) ICML (15) ICLR (7) AAAI (2) ACL (1) AISTATS (1) IJCAI (1) RSS (1)

Top co-authors

Matteo Hessel (15) Arthur Guez (10) Andre Barreto (10) Hado P van Hasselt (10) Zhongwen Xu (8) Hado van Hasselt (8) Nicolas Heess (7) Tom Schaul (7) Satinder P. Singh (6) Junhyuk Oh (6)

Research topics

Reinforcement Learning (1)

Keywords

reinforcement learning (16) value function (11) model-based reinforcement learning (9) deep reinforcement learning (6) temporal-difference learning (5) neural network (4) successor feature (3) value function approximation (3) credit assignment (3) representation learning (3) exploration exploitation (3) policy improvement (3) transfer learning (3) value iteration (3) policy gradient (3) hierarchical reinforcement learning (3) continuous control (3) function approximation (3) online learning (3) monte carlo tree search (3)

Papers

Learning by Directional Gradient Descent ICLR 2022 Bootstrapped Meta-Learning ICLR 2022 Planning in Stochastic Environments with a Learned Model ICLR 2022 Policy improvement by planning with Gumbel ICLR 2022 Muesli: Combining Improvements in Policy Optimization ICML 2021 The Value-Improvement Path: Towards Better Representations for Reinforcement Learning AAAI 2021 Discovery of Options via Meta-Learned Subgoals NIPS 2021 Proper Value Equivalence NIPS 2021 Online and Offline Reinforcement Learning by Planning with a Learned Model NIPS 2021 Self-Consistent Models and Values NIPS 2021 Expected Eligibility Traces AAAI 2021 Learning and Planning in Complex Action Spaces ICML 2021 Behaviour Suite for Reinforcement Learning ICLR 2020 What Can Learned Intrinsic Rewards Capture? ICML 2020 Discovering Reinforcement Learning Algorithms NIPS 2020 The Value Equivalence Principle for Model-Based Reinforcement Learning NIPS 2020 Value-driven Hindsight Modelling NIPS 2020 Meta-Gradient Reinforcement Learning with an Objective Discovered Online NIPS 2020 A Self-Tuning Actor-Critic Algorithm NIPS 2020 The Option Keyboard: Combining Skills in Reinforcement Learning NIPS 2019 Discovery of Useful Questions as Auxiliary Tasks NIPS 2019 An Investigation of Model-Free Planning ICML 2019 Credit Assignment Techniques in Stochastic Computation Graphs AISTATS 2019 Universal Successor Features Approximators ICLR 2019 Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement ICML 2018 Implicit Quantile Networks for Distributional Reinforcement Learning ICML 2018 Meta-Gradient Reinforcement Learning NIPS 2018 Learning to search with MCTSnets ICML 2018 Distributed Prioritized Experience Replay ICLR 2018 FeUdal Networks for Hierarchical Reinforcement Learning ICML 2017 Decoupled Neural Interfaces using Synthetic Gradients ICML 2017 A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning NIPS 2017 Successor Features for Transfer in Reinforcement Learning NIPS 2017 Imagination-Augmented Agents for Deep Reinforcement Learning NIPS 2017 Natural Value Approximators: Learning when to Trust Past Estimates NIPS 2017 The Predictron: End-To-End Learning and Planning ICML 2017 Asynchronous Methods for Deep Reinforcement Learning ICML 2016 Learning values across many orders of magnitude NIPS 2016 Learning Continuous Control Policies by Stochastic Value Gradients NIPS 2015 Smooth UCT Search in Computer Poker IJCAI 2015 Fictitious Self-Play in Extensive-Form Games ICML 2015 Universal Value Function Approximators ICML 2015 Deterministic Policy Gradient Algorithms ICML 2014 Bayes-Adaptive Simulation-based Search with Value Function Approximation NIPS 2014 Concurrent Reinforcement Learning from Customer Interactions ICML 2013 Efficient Bayes-Adaptive Reinforcement Learning using Sample-Based Search NIPS 2012 Learning to Win by Reading Manuals in a Monte-Carlo Framework ACL 2011 Monte-Carlo Planning in Large POMDPs NIPS 2010 Bootstrapping from Game Tree Search NIPS 2009 Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation NIPS 2009 High Performance Outdoor Navigation from Overhead Data using Imitation Learning RSS 2008