Stars
The Multi-Agent RLRM (Reinforcement Learning with Reward Machines) Framework is a library designed to facilitate the formulation of multi-agent problems and solve them through reinforcement learnin…
MAPRL (Multiagent Planning for Reinforcement Learning) is a framework that integrates Reward Machines (RMs) with Partial-Order Planning (POP) to enhance coordination in multi-agent reinforcement le…
A list of Matlab's files to solve some common robotics' problems (a minimalist GUI is also provided in some cases)
An OpenAIGym-based framework allowing to test Delay-Aware Deep Reinforcement Learning algorithms for cooperative multi-UAV systems in fully customizable scenarios (e.g., coverage maximization, trac…
Deep Q-Network (DQN) and Fitted Q-Iteration (FQI) tutorial for RL Summer School 2023 and 2026
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
An OpenaAIGym-based framework allowing to test hybrid approaches (RL + path planning) for multi-UAV systems that are supposed to provide smart services.
The AIPlan4EU Unified Planning Library