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Nick Hawes

University of Oxford, UK

16 papers at tracked venues · 6 at CORE A* · active 2024–2026

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Venues

IROS ×3NeurIPS ×3AAAI ×2AAMAS ×2ICRA ×2ECAI ×1ICAPS ×1ICML ×1IJCAI ×1

Frequent coauthors

Alexander Rutherford
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Yang You
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Harry Mead
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Alex Stephens
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Alex Schutz
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Yuanjie Lu
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Rhys Howard
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Iman Nematollahi
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Benedetta Flammini
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Clarissa Costen
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Matthew Budd
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Papers

  1. Scalable Solution Methods for Dec-POMDPs with Deterministic Dynamics
    AAAI 2026 ·
    Yang You
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  2. A Finite-State Controller Based Offline Solver for Deterministic POMDPs
    IJCAI 2025 ·
    Alex Schutz
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  3. Decremental Dynamics Planning for Robot Navigation
    IROS 2025 ·
    Yuanjie Lu
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  4. Generating Causal Explanations of Vehicular Agent Behavioural Interactions with Learnt Reward Profiles
    ICRA 2025 ·
    Rhys Howard
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  5. Improving Regret Approximation for Unsupervised Dynamic Environment Generation
    NeurIPS 2025 ·
    Harry Mead
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  6. LUMOS: Language-Conditioned Imitation Learning with World Models
    ICRA 2025 ·
    Iman Nematollahi
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  7. Multi-Agent Pickup and Delivery with Mobile Pickups
    IROS 2025 ·
    Benedetta Flammini
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  8. Partially Observable Monte-Carlo Graph Search
    ICAPS 2025 ·
    Yang You
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  9. Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
    ICML 2025 ·
    Harry Mead
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  10. Hierarchical Planning for Resource-Constrained Long-Term Monitoring Missions in Time-Varying Environments
    ECAI 2024 ·
    Alex Stephens
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  11. JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
    AAMAS 2024 ·
    Alexander Rutherford
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  12. JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
    NeurIPS 2024 ·
    Alexander Rutherford
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  13. Multi-Robot Allocation of Assistance from a Shared Uncertain Operator
    AAMAS 2024 ·
    Clarissa Costen
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  14. No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
    NeurIPS 2024 ·
    Alexander Rutherford
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  15. Planning for Long-Term Monitoring Missions in Time-Varying Environments
    IROS 2024 ·
    Alex Stephens
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  16. Stop! Planner Time: Metareasoning for Probabilistic Planning Using Learned Performance Profiles
    AAAI 2024 ·
    Matthew Budd
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