SMAC download | SourceForge.net

SMAC (StarCraft II Multi-Agent Challenge) is a benchmark environment for cooperative multi-agent reinforcement learning (MARL), based on real-time strategy (RTS) game scenarios in StarCraft II. It allows researchers to test algorithms where multiple units (agents) must collaborate to win battles against built-in game AI opponents. SMAC provides a controlled testbed for studying decentralized execution and centralized training paradigms in MARL.

Features

Focuses on decentralized multi-agent cooperation challenges
Provides a variety of tactical combat scenarios in StarCraft II
Supports partial observability and limited communication among agents
Integrates with PyMARL and other MARL libraries for training
Includes a standard benchmark for evaluating MARL algorithms
Offers tools for measuring performance and analyzing agent coordination

Project Samples

Project Activity

See All Activity >

License

MIT License

Follow SMAC

SMAC Web Site

Other Useful Business Software

Find Hidden Risks in Windows Task Scheduler

Free diagnostic script reveals configuration issues, error patterns, and security risks. Instant HTML report.

Windows Task Scheduler might be hiding critical failures. Download the free JAMS diagnostic tool to uncover problems before they impact production—get a color-coded risk report with clear remediation steps in minutes.

Download Free Tool

Rate This Project

User Reviews

Be the first to post a review of SMAC!

Additional Project Details

Programming Language

Python

Related Categories

Python Reinforcement Learning Frameworks

Registered

2025-03-13

Similar Business Software

Vertex AI

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery...

See Software
Ango Hub

Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare...

See Software
OORT DataHub

Data Collection and Labeling for AI Innovation. Transform your AI development with our decentralized platform that connects you to worldwide data contributors. We combine global crowdsourcing with blockchain verification to deliver diverse, traceable datasets. Global Network: Ensure AI...

See Software
TF-Agents

TensorFlow Agents (TF-Agents) is a comprehensive library designed for reinforcement learning in TensorFlow. It simplifies the design, implementation, and testing of new RL algorithms by providing well-tested modular components that can be modified and extended. TF-Agents enables fast code...

See Software
Hugging Face

Hugging Face is a leading platform for AI and machine learning, offering a vast hub for models, datasets, and tools for natural language processing (NLP) and beyond. The platform supports a wide range of applications, from text, image, and audio to 3D data analysis. Hugging Face fosters...

See Software
Gymnasium

Gymnasium is a maintained fork of OpenAI’s Gym library, providing a standard API for reinforcement learning and a diverse collection of reference environments. The Gymnasium interface is simple, pythonic, and capable of representing general RL problems, and has a compatibility wrapper for old...

See Software