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David Silver

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

Achievements

🐝 Cross-Pollinator (5) 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (22) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (14) 🏠 Conference Loyalist (23) 🌟 Keyword Trendsetter Combo (6) 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown 🌱 Topic Pioneer 🧬 Topic Evolution πŸ† Keyword Champion (3) πŸ† Grand Slam πŸ”¬ Deep Specialist (26) πŸ—ƒοΈ Keyword Collector (85) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (15) πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ’Ž 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