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Satinder Singh

48 papers · 2000–2025 · 11 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (11) 🌈 Renaissance Researcher (9) 🐝 Cross-Pollinator (14) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (25) πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (6) πŸ† Grand Slam πŸ‘₯ Mega-Team (27) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (13) πŸ† Keyword Champion (2) πŸš€ Conference Pioneer ❓ The Questioner (2) ⚑ Prolific Year (6) πŸ’Ž Century Club (48) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (187)

Conferences

NIPS (10) ICML (9) ICLR (7) IJCAI (7) AAAI (6) AISTATS (4) ACL (1) ALT (1) COLING (1) EACL (1) EMNLP (1)

Top co-authors

Honglak Lee (9) Nan Jiang (8) Junhyuk Oh (8) Richard Lewis (7) Tom Zahavy (6) Edmund Durfee (5) Alex Kulesza (5) Xiaoxiao Guo (4) Janarthanan Rajendran (4) Sebastian Flennerhag (4)

Research topics

Reinforcement Learning (2)

Keywords

reinforcement learning (10) multi-agent system (4) neural network (3) markov decision process (3) model-based reinforcement learning (3) intrinsic reward (3) reward function (3) spectral learning (3) reward function learning (2) model-free reinforcement learning (2) predictive state representation (2) query optimization (2) deep reinforcement learning (2) text classification (2) attention mechanism (2) recurrent neural network (2) singular value decomposition (2) supervised learning (2) active learning (2) low-rank approximation (2)

Papers

Mastering Board Games by External and Internal Planning with Language Models ICML 2025
Genie: Generative Interactive Environments ICML 2024
Human-Timescale Adaptation in an Open-Ended Task Space ICML 2023
Discovering Evolution Strategies via Meta-Black-Box Optimization ICLR 2023
ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs ICML 2023
Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality ICLR 2023
Composing Task Knowledge With Modular Successor Feature Approximators ICLR 2023
In-context Reinforcement Learning with Algorithm Distillation ICLR 2023
Adaptive Pairwise Weights for Temporal Credit Assignment AAAI 2022
On the Expressivity of Markov Reward (Extended Abstract) IJCAI 2022
Bootstrapped Meta-Learning ICLR 2022
Discovering a set of policies for the worst case reward ICLR 2021
Efficient Querying for Cooperative Probabilistic Commitments AAAI 2021
Reinforcement Learning of Implicit and Explicit Control Flow Instructions ICML 2021
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment IJCAI 2021
How Should an Agent Practice? AAAI 2020
Querying to Find a Safe Policy under Uncertain Safety Constraints in Markov Decision Processes AAAI 2020
Behaviour Suite for Reinforcement Learning ICLR 2020
Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement AAAI 2020
What Can Learned Intrinsic Rewards Capture? ICML 2020
Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles AISTATS 2020
Learning to Communicate and Solve Visual Blocks-World Tasks AAAI 2019
No-Press Diplomacy: Modeling Multi-Agent Gameplay NIPS 2019
Hindsight Credit Assignment NIPS 2019
Discovery of Useful Questions as Auxiliary Tasks NIPS 2019
Learning End-to-End Goal-Oriented Dialog with Multiple Answers EMNLP 2018
Completing State Representations using Spectral Learning NIPS 2018
On Learning Intrinsic Rewards for Policy Gradient Methods NIPS 2018
Markov Decision Processes with Continuous Side Information ALT 2018
Self-Imitation Learning ICML 2018
Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes IJCAI 2018
Predicting Counselor Behaviors in Motivational Interviewing Encounters EACL 2017
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning ICML 2017
Understanding and Predicting Empathic Behavior in Counseling Therapy ACL 2017
Value Prediction Network NIPS 2017
Repeated Inverse Reinforcement Learning NIPS 2017
Deep Learning for Reward Design to Improve Monte Carlo Tree Search in ATARI Games IJCAI 2016
The Dependence of Effective Planning Horizon on Model Accuracy IJCAI 2016
Commitment Semantics for Sequential Decision Making under Reward Uncertainty IJCAI 2016
On Structural Properties of MDPs that Bound Loss Due to Shallow Planning IJCAI 2016
Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015
Abstraction Selection in Model-based Reinforcement Learning ICML 2015
Action-Conditional Video Prediction using Deep Networks in Atari Games NIPS 2015
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning NIPS 2014
Low-Rank Spectral Learning AISTATS 2014
Characterizing EVOI-Sufficient k-Response Query Sets in Decision Problems AISTATS 2014
Reward Mapping for Transfer in Long-Lived Agents NIPS 2013
Automatic Optimization of Dialogue Management COLING 2000