41 datasets found

The dataset used in the paper is a set of joint observations that are used to train the generative model. The dataset is used to evaluate the performance of the proposed method...

The dataset used in the paper is a multi-agent environment where agents learn to coordinate their actions to achieve a common goal. The dataset is used to evaluate the proposed...

The dataset used in the research paper is a multi-agent environment for training the car agent, allowing it to learn human behaviors through multimodal sensory data.

The dataset is used for multi-UAV speed control with collision avoidance and handover-aware cell association. The dataset is used to optimize the autonomous motion of multiple...

The dataset is used to evaluate the state-space distribution of an Age-of-Information network.

A dataset for distributed reinforcement learning problem in which a network of multiple agents aim to cooperatively maximize the globally averaged return through communication...

DARLEI is a framework that combines evolutionary algorithms with parallelized reinforcement learning for efficiently training and evolving populations of UNIMAL agents.

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.