8 datasets found

The dataset used in the paper for training a recurrent spatio-temporal network for hyperbolic conservation laws.

A Multi-Agent Reinforcement Learning (MARL) framework for cooperative data collection to build a 3D mapping of the disaster scene using agents present around the incident zone...

Reward-Sharing Relational Networks in Multi-Agent Reinforcement Learning as a Framework for Emergent Behavior

A Drone Swarm Search environment, based on PETTINGZOO, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms.

The dataset used in this paper is a set of five game-theoretic tasks (Harmony Game, Hawk-Dove, Stag-Hunt, Prisoners Dilemma and Battle of the Exes) with seven different agent...

The dataset used in the paper is a multi-agent reinforcement learning environment, where agents need to communicate with each other to achieve their goals.

To overcome the sim-to-real gap in reinforcement learning (RL), learned policies must maintain robustness against environmental uncertainties. While robust RL has been widely...

The Google Research Football environment is a reinforcement learning experimental platform focused on training agents to play football.