MARL-BattleGrounds
No liveness check has reached it yet; it is registered on GitHub and PyPI and has been in the index since 10 Oct 2026. How this is checked
MARL-BattleGrounds is an Apache-2.0 open-source benchmark for heterogeneous and competitive multi-agent reinforcement learning. It provides JAX-native environments and scenarios for researchers and developers evaluating multi-agent systems.
Inferred · not functionally tested
Overview
6 featuresPurpose: Benchmarking heterogeneous and competitive multi-agent reinforcement learning systems.
Inferred · not functionally tested
Audience: reinforcement learning researchers and developers
Inferred · not functionally tested
Functions: Unknown
Interfaces: API: unknown · MCP: unknown · CLI: indicated (inferred, not tested) · Self-hosting: indicated (inferred, not tested)
Recorded constraints: pricing: open_source · license: Apache-2.0 · platforms: CLI, WEB · deployment: browser, cli, self_hosted
Constraint provenance is unknown; confirm requirements with the publisher.
Record sources: marl-battlegrounds.com · github.com. These links do not verify the individual claims.
MARL-BattleGrounds sits in PulseGate's Frameworks & runtimes category. Inferred · not functionally tested: It focuses on benchmarking heterogeneous and competitive multi-agent reinforcement learning systems. Inferred · not functionally tested: MARL-BattleGrounds is an open-source project aimed at reinforcement learning researchers and developers. Basis unknown · not verified: MARL-BattleGrounds is open source under the Apache-2.0 license. Basis unknown · not verified: It runs on the web and the command line, and it can be self-hosted.
Oceans Systems Lab builds and maintains MARL-BattleGrounds, and it first shipped in 2026. Inferred · not functionally tested: Among its 6 catalogued features are JAX-native environments, multi-agent scenarios, and competitive gameplay.
Summary written by a language model from the project’s public pages.
Tasks: Inferred · not functionally tested
- JAX-native environments
- Multi-agent scenarios
- Competitive gameplay
- Heterogeneous agents
- Team deathmatch
- Benchmark evaluation
Topics: Inferred · not functionally tested
Built with & integrations
Trust & compliance
Indexing history
1What PulseGate has recorded for this listing
- Indexed10 Oct · 03:12 UTCmarl-battlegrounds seen via PyPI Bulk EnumeratorSource: PyPI Bulk Enumerator · Open
Frequently asked questions about MARL-BattleGrounds
- What does MARL-BattleGrounds do?
- Inferred · not functionally tested: MARL-BattleGrounds focuses on benchmarking heterogeneous and competitive multi-agent reinforcement learning systems. It is catalogued under Frameworks & runtimes on PulseGate.
- Who is MARL-BattleGrounds for?
- Inferred · not functionally tested: MARL-BattleGrounds is an open-source project built for reinforcement learning researchers and developers.
- Is MARL-BattleGrounds free?
- Basis unknown · not verified: Yes — MARL-BattleGrounds is open source under the Apache-2.0 license and free to use.
- What platforms does MARL-BattleGrounds run on?
- Basis unknown · not verified: MARL-BattleGrounds runs on the web and the command line. It can also be self-hosted.
- Is MARL-BattleGrounds still maintained?
- Unverified. MARL-BattleGrounds has not been re-checked since it entered the index, so there is no finding either way — and only a positive finding would say otherwise.
- Who develops MARL-BattleGrounds?
- MARL-BattleGrounds is developed by Oceans Systems Lab.
- When did MARL-BattleGrounds launch?
- MARL-BattleGrounds first shipped in 2026.
- Is MARL-BattleGrounds open source?
- Basis unknown · not verified: Yes — MARL-BattleGrounds is open source under the Apache-2.0 license, developed on GitHub.
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