LI
opendilab/LightZero
[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)
1.6k 188 +0/wk
GitHub
alpha-beta-pruning alphazero atari board-game board-games continuous-control efficientzero gomoku gumbel-muzero gym mcts mcts-algorithm
Trend
0
Star & Fork Trend (19 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
opendilab/LightZero has +0 stars this period . Velocity data will be available after more historical data is collected.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | LightZero | agent-safehouse | Semi-supervised-learning | poker_ai |
|---|---|---|---|---|
| Stars | 1.6k | 1.6k | 1.6k | 1.6k |
| Forks | 188 | 59 | 213 | 409 |
| Weekly Growth | +0 | +7 | +0 | +1 |
| Language | Python | Shell | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | Apache-2.0 | MIT | NOASSERTION |
Capability Radar vs agent-safehouse
LightZero
agent-safehouse
Maintenance Activity 100
Last code push 3 days ago.
Community Engagement 60
Fork-to-star ratio: 12.0%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.