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Multi-Agent Reinforcement Learning with a Hierarchy of Reward Machines
The dataset used in the paper is a hierarchical structure of propositions, where a higher-level proposition is a temporal abstraction of lower-level propositions. Each... -
Multi-Agent Reinforcement Learning
The dataset used in the paper is a collection of 21 diverse multi-agent tasks in four environments: level-based foraging, boulder-push, multi-robot warehouse, and multi-agent... -
Half Field Offense
The Half Field Offense environment is a multi-agent reinforcement learning problem where multiple agents interact in a soccer-like environment. -
Multi-Team Predator-Prey
The Multi-Team Predator-Prey environment is a multi-agent reinforcement learning problem where multiple predators and prey interact in a grid-based environment. -
StarCraft II micromanagement tasks
The dataset used in the paper is the StarCraft II micromanagement tasks. -
Multi-Agent Particle Environment and Google Research Football Environment
Multi-agent particle environment and Google Research football environment. -
ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward
Modern multi-agent reinforcement learning frameworks rely on centralized training and reward shaping to perform well. However, centralized training and dense rewards are not... -
Google Research Football
The Google Research Football environment is a reinforcement learning experimental platform focused on training agents to play football. -
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Multi-agent environments for training and testing the proposed Multi-Agent Actor-Critic (MAAC) algorithm.
