Multi-Objective Reinforcement Learning algorithms implementations.

Multi-objective Gymnasium environments for reinforcement learning

A Predator-Prey-Grass multi-objective multi-agent gridworld environment implemented with Farama's Gymnasium, PettingZoo and MOMAland, featuring dynamic agent spawning and deletion, where agents have partial observability.

Code for the paper Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer - ICML 2022

Multi-Objective Multi Agent Reinforcement Learning (MOMARL) experiments.