34 datasets found

The dataset used in this paper is a distributed logistic regression problem.

The dataset used in the paper is a 2-D environment with a starting region S, a destination region D, and an obstacle region ∆. The environment is described by a starting region...

A large-scale dataset of No Press Diplomacy games, containing more than 150,000 human games.

The dataset used in the paper is a multi-agent communication framework, which is used to evaluate the performance of different communication strategies in a multi-agent system.

The distributed constraint solver application is based on a local search algorithm called Distributed Penalty-driven Local search (DisPeL) as its underlying constraint solver.

A set of 25 Warehouse Games, each resembling a situation of patrolling a warehouse building.

The dataset used in the paper is a multi-agent system with competing online learning agents. The dataset is used to evaluate the proposed pricing mechanism for resource...

NGSIM is a collection of video-transcribed datasets of vehicle trajectories on US-101, Lankershim Blvd. in Los Angeles, I-80 Emeryville. It contains approximately 45 minutes of...

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

The BabyAI levels dataset is a collection of levels with increasing degrees of complexity, where agents need to solve tasks in a simulated environment.

The BabyAI dataset is a collection of sequential decision-making problems where agents need to navigate and act in a simulated environment.

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 this paper is a nonlinear positive multi-agent system with sector input nonlinearities.

This paper introduces Trajectron, a probabilistic multi-agent trajectory modeling framework.

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.

Pommerman is a 2-vs-2 game environment introduced in 2018, and is a modified version of the popular game 'Bomberman'. It is a good testbed for RL, because the environment...

The dataset used in the paper is a discrete-time blended dynamics theorem, which is a discrete-time version of the blended dynamics theorem for the use of designing distributed...