| Jan 1, 2024 |  “Intrinsic Language-Guided Exploration for Complex Long-Horizon Robotic Manipulation Tasks “ has been accepted in ICRA! It discusses how LLMs can be used to guide exploration in long-horizon, sparse-reward tasks. |
| Oct 29, 2023 | Our paper “Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning” now accepted in TMLR! Pareto-AC learns Pareto-optimal Equilibria in many MARL environments and reaches new sota results. |
| May 29, 2023 | 📖: Pre-print version of our book on MARL was just released! Find it here: Multi-Agent Reinforcement Learning: Foundations and Modern Approaches |
| Jan 18, 2023 | My NVIDIA internship resulted in “Planning with Occluded Traffic Agents using Bi-Level Variational Occlusion Models” which was just accepted in ICRA 2023! |
| Oct 29, 2022 | Preprints of my two new papers are online! My NVIDIA internship paper on AV occlusions and Pareto Actor-Critic: a new algorithm for MARL. |
| Jun 23, 2022 | I joined NVIDIA Research for a three month internship on autonomous vehicles! |
| Dec 20, 2021 | Our paper titled “Decoupling Exploitation and Intrinsically-Motivated Exploration in Reinforcement Learning” has been accepted in AAMAS 2022! |
| Sep 27, 2021 | Another paper accepted at NeurIPS 2021: Agent Modelling under Partial Observability for Deep Reinforcement Learning. |
| Jul 29, 2021 | Our benchmarking paper for MARL has been accepted at NeurIPS 2021: Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks. |
| May 10, 2021 | Two new papers accepted at ICML 2021: Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing and Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning. |
| Dec 20, 2020 |  My blog post on two new environments for MARL has just been posted in our groups webpage. |
| Dec 8, 2020 | Our paper, Shared Experience Actor-Critic for Multi-Agent Reinforcement Learning, has been accepted and published in Neural Information Processing Systems (NeurIPS 2020). |