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Object Collection Game
The object collection game is a simple 2D video game that requires the agent to collect objects that move from the top of the screen to the bottom. -
Multi-agent environments
The dataset used in the paper is a set of procedurally generated levels for the four distinct multi-agent environments: HarvestPatch, Traffic Navigation, Overcooked, and Capture... -
SMIX(λ): Enhancing Centralized Value
SMIX(λ) is a method for cooperative multi-agent reinforcement learning that uses an off-policy training approach to estimate a centralized value function. -
Simple Spread environment
The dataset used in the paper is the Simple Spread environment, which consists of N agents and N landmarks. The aim of teamed agents is to learn covering all the landmarks while... -
StarCraft II Multi-Agent Challenge (SMAC) dataset
The dataset used in the paper is the StarCraft II Multi-Agent Challenge (SMAC) dataset, which consists of 8 tasks with different difficulty levels. The dataset is used to... -
Room Clearance with Feudal Hierarchical Reinforcement Learning
A new simulation environment designed as a simple testbed for demonstrating the utility of RL as a tool for concept analysis with military applications as well as to aid with... -
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... -
StarCraft II unit micromanagement benchmark
The dataset used in the paper is a multi-agent reinforcement learning dataset, where agents learn to coordinate their actions to achieve a common goal. -
Offline Fictitious Self-Play for Competitive Games
Offline Fictitious Self-Play for Competitive Games -
Simultaneous Move Games via Equilibrium Approximation
The dataset used in the paper is a stochastic game, specifically a simultaneous-move game, with multiple agents and a finite horizon. -
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... -
Multi-Agent Particle Environment (MAPE)
Multi-Agent Particle Environment (MAPE) game environment -
Hierarchical RNNs-Based Transformers MADDPG
Hierarchical RNNs-Based Transformers MADDPG for Mixed Cooperative-Competitive Environments -
Complex Topology
Packet routing environments for cooperative multi-agent reinforcement learning -
Moderate Topology
Packet routing environments for cooperative multi-agent reinforcement learning -
Simple Topology
Packet routing environments for cooperative multi-agent reinforcement learning -
Packet Routing Domain
Packet routing environments for cooperative multi-agent reinforcement learning