Critical Ranger FFM¶

Critical Ranger FFM is the first concrete project under the rl-sim-labs namespace. It is a toy forest-fire / PufferLib reinforcement-learning experiment focused on zone-control policies, not a standalone namespace yet.

Current role in this namespace¶

Critical Ranger is the seed RL simulation lab:

• environment: forest-fire simulation with self-organized dynamics;
• action model: no-op or thin one selected zone at a decision tick;
• evaluation target: reduce mega-fire frequency versus honest simple baselines;
• constraints: preserve acceptable tree density and stay within intervention budget;
• evidence posture: metrics and anti-cheat gates decide belief, not training reward alone.

Active roadmap¶

The active path is the Zone-Control RL MVP. The prior switch-point / single-cell efficacy path is parked as diagnostic infrastructure.

Current next implementation gate from the source note:

#54 — zone-control action contract fixtures

That slice is intentionally narrow: deterministic zone indexing, no-op action, one-zone thinning contract, decision interval semantics, and CPU-safe fixture tests.

Promotion boundary¶

Do not promote Critical Ranger to its own namespace yet. It should remain an entity/project inside rl-sim-labs until it has an independent audience, raw experiment corpus, recurring reports, multiple durable document types, and a clear covers/not-covered boundary.

Source¶

Compiled from Projects/Critical Ranger FFM/Index.md.