Nick Hawes

19 papers · 2015–2026 · 6 conferences · across top CS/AI conferences

Achievements

+8 more ↓

🌍 Conference Polyglot (6) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (10)

🌍 Conference Polyglot (6) 🏃 Academic Marathon (10) 🌈 Renaissance Researcher (5) 🤝 Dynamic Duo (17) 👥 Mega-Team (21) 🔥 Unstoppable (8) 💎 Century Club (18) 🗃️ Keyword Collector (87)

Conferences

NIPS (6) AAAI (5) IJCAI (4) CORL (2) AISTATS (1) ICML (1)

Top co-authors

Bruno Lacerda (18) Marc Rigter (6) Clarissa Costen (3) Matthew Budd (2) Timon Willi (2) Jakob Foerster (2) Yang You (2) Alex Schutz (2) Paul Duckworth (2) Mikayel Samvelyan (1)

Keywords

markov decision process (5) gaussian process (2) model-based reinforcement learning (2) reinforcement learning (2) offline reinforcement learning (2) monte carlo tree search (2) bayesian learning (1) adversarial training (1) policy optimization (1) epistemic uncertainty (1) uncertainty quantification (1) human-robot interaction (1) mechanism design (1) robust planning (1) bellman equation (1) bayesian reinforcement learning (1) exploration-exploitation tradeoff (1) policy search (1) dynamic programming (1) bayesian inference (1)

Papers

Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics AAAI 2026 A Finite-State Controller Based Offline Solver for Deterministic POMDPs IJCAI 2025 Return Capping: Sample Efficient CVaR Policy Gradient Optimisation ICML 2025 Stop! Planner Time: Metareasoning for Probabilistic Planning Using Learned Performance Profiles AAAI 2024 No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery NIPS 2024 JaxMARL: Multi-Agent RL Environments and Algorithms in JAX NIPS 2024 Multi-Unit Auctions for Allocating Chance-Constrained Resources AAAI 2023 One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning NIPS 2023 Monte Carlo Tree Search with Boltzmann Exploration NIPS 2023 Planning with Hidden Parameter Polynomial MDPs AAAI 2023 Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments CORL 2022 Shared Autonomy Systems with Stochastic Operator Models IJCAI 2022 RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning NIPS 2022 Risk-Averse Bayes-Adaptive Reinforcement Learning NIPS 2021 Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes AAAI 2021 Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes CORL 2020 Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints IJCAI 2019 Efficient Bayesian Methods for Counting Processes in Partially Observable Environments AISTATS 2018 Optimal Policy Generation for Partially Satisfiable Co-Safe LTL Specifications IJCAI 2015