Hanabi Learning Environment
https://github.com/google-deepmind/hanabi-learning-environment
DeepMind's Hanabi Learning Environment — a benchmark for cooperative multi-agent agents under partial observability and theory-of-mind. Players see each other's cards but not their own; success requires modeling teammates' beliefs. Bard (Bowling et al. 2020) described Hanabi as 'a new frontier for AI research'. Used in OpenAI ad hoc team-play papers and DeepMind's Bayesian Action Decoder.
At a glance
- Type
- Cooperative multi-agent partial-observability card-game benchmark
- Tier
- T3
- Section
- Memory benchmarks & evaluation
- Created
- 2019-02 (Bard et al. arXiv 1902.00506)
- Latest release
- not applicable — not OSS
- License
- Apache-2.0
- GitHub
- 700★ C++/Python
- Pricing
- not applicable — open benchmark; free to use
- Funding
- not applicable — not commercial
Taxonomy
- storage
- n/a
- retrieval
- n/a
- persistence
- n/a
- update
- read-only
- unit
- n/a
- governance
- n/a
- conflict
- n/a
When to use
Optimised for: not applicable - eval dataset, not a system
Anti-fit: not applicable - eval dataset, not a system
Pros & cons
Pros
Tests cooperation + partial-observability + theory-of-mind simultaneously; cooperative-only (no zero-sum complication); strong DeepMind pedigree.
Cons
Discrete card-game scope limits visual-perception relevance; performance ceilings against expert humans not yet reached.
Claims & capabilities
Bowling et al. 2020 — described Hanabi as 'new frontier for AI'; canonical cooperative-MARL benchmark; ad-hoc team-play benchmark used by Strouse et al. 2021
Technical surface
- API surface
- not applicable — eval dataset, not a system
- Backend storage
- not applicable — eval dataset, not a system
- Deployment
- not applicable — run locally
- Embedding model
- not applicable — eval dataset, not a system
- Multi-tenancy
- not applicable — eval dataset, not a system
- MCP
- not applicable — benchmark / evaluation harness
- A2A
- not applicable — benchmark / evaluation harness
- OpenTelemetry
- not applicable — benchmark / evaluation harness
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