Activité

  • Chercheur postdoctoral: juin 2021 - déc. 2023

Prépublications

Articles de conférence et de revue

2024

  1. Mastering Memory Tasks with World Models
    , , et
    International Conference on Learning Representations (ICLR), 2024. [Oral presentation.]
    #RL, #DL
    [openreview]

  2. Intelligent Switching for Reset-Free RL
    , , Glen Berseth et
    International Conference on Learning Representations (ICLR), 2024.
    #RL
    [openreview]

  3. Learning Conditional Policies for Crystal Design Using Offline Reinforcement Learning
    , Santiago Miret, , Mariano Phielipp, et
    Digital Discovery Journal, 2024.
    #RL
    [openreview]

2023

  1. Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning
    , , Ida Momennejad, Harm van Seijen et
    Conference on Lifelong Learning Agents (CoLLAs), 2023.
    [Deep Reinforcement Learning Workshop, NeurIPS, 2022]
    #RL
    [arXiv]

  2. Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi
    , , , Miao Liu et
    Conference on Lifelong Learning Agents (CoLLAs), 2023.
    #RL
    [paper]

  3. Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning
    , , Amit Sinha, Mohammad Amini, , Aditya Mahajan et
    Conference on Lifelong Learning Agents (CoLLAs), 2023.
    #RL
    [arXiv]

  4. Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning
    , Yangchen Pan, Chenjun Xiao, et
    Conference on Uncertainty in Artificial Intelligence (UAI), 2023.
    #RL
    [arXiv]

2022

  1. Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods
    , , , Ida Momennejad, et Harm van Seijen
    International Conference on Machine Learning (ICML), 2022.
    #RL
    [arXiv], [code]