Informationally Mosaic Reinforcement Learning (Preprint: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=nargncAAAAAJ&citation_for_view=nargncAAAAAJ:W7OEmFMy1HYC)
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Updated
Jan 10, 2022 - Python
Informationally Mosaic Reinforcement Learning (Preprint: https://scholar.google.com/citations?view_op=view_citation&hl=en&user=nargncAAAAAJ&citation_for_view=nargncAAAAAJ:W7OEmFMy1HYC)
This repository includes the implementation of the ICML 2024 paper titled "Open Ad Hoc Teamwork with Cooperative Game Theory."
Safe and Robust Experience Sharing for Deterministic Policy Gradient Algorithms
Stubborn: An Environment for Evaluating Stubbornness between Agents with Aligned Incentives
A minimalist multi-agent implementation of the social dilemma problem with governance kernels
Proximal Policy Optimization algorithm applied to the Harvest Game, a multi-agent environment
A multi-agent deep reinforcement learning model to de-traffic our lives
Python Implementation of the RoboCup Keepaway suitable for Deep Reinforcement Learning.
Heterogeneous Multi-agent Version of Highway-env
Library/Source code for different components used in Modobot planner
Repository for code pertaining to the Multi-agent RL project at Computer Society IEEE NITK Student Branch
A research platform to develop Cyberdefense Multi-Agent Systems combining Multi-Agent-Reinforcement Learning to assist designers to find a suited organization regarding constraints and goals
HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messaging (Paper: https://ala2021.vub.ac.be/papers/ALA2021_paper_35.pdf)
Enabling UAVs to navigate corridors efficiently, aiming to minimize travel time to their destinations.
Minimal frameworks for multi-agent reinforcement learning with deep neaural network.
This project is a computer simulation of a multi-agent extended prisoner’s dilemma using manipulation. The aim is to investigate if the outcome for all agents is better with or without the possibility of manipulation.
Learnable MAPF. “Distributed Heuristic Multi-Agent Path Finding with Communication” (DHC) algorithm from ICRA 2021 is implemented and benchmarked in out-of-distribution (OOD) scenarios. A new robust training loop to handle communication failures is introduced.
Pytorch implementation of MADDPG algorithm
Udacity deep reinforcement learning collaboration and competition project
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