| name: cascade-containment |
| version: "1.0.0" |
| description: > |
| An RL benchmark for epidemic containment policy under uncertainty. |
| A city health authority must allocate limited resources across districts |
| to contain a spreading outbreak — with delayed data, resource scarcity, |
| and cascading hospital stress. Generalises to wildfire deployment, |
| cyberattack isolation, and misinformation containment. |
| |
| author: SST-Team |
| license: MIT |
|
|
| server: |
| module: server.app |
| app: app |
| port: 7860 |
| dockerfile: Dockerfile |
|
|
| action: |
| type: object |
| class: ContainmentAction |
| fields: |
| action_type: |
| type: string |
| description: "One of: 'test', 'restrict', 'allocate'" |
| enum: [test, restrict, allocate] |
| district_id: |
| type: integer |
| description: "Target district index (0-indexed)" |
| minimum: 0 |
|
|
| observation: |
| type: object |
| class: CityObservation |
| fields: |
| districts: |
| type: array |
| description: "Per-district state visible to agent" |
| items: |
| type: object |
| fields: |
| district_id: |
| type: integer |
| reported_infection_rate: |
| type: number |
| minimum: 0.0 |
| maximum: 1.0 |
| growth_rate_hint: |
| type: number |
| minimum: 0.0 |
| maximum: 1.0 |
| hospital_capacity_remaining: |
| type: number |
| minimum: 0.0 |
| maximum: 1.0 |
| population_density: |
| type: number |
| minimum: 0.0 |
| maximum: 1.0 |
| tested_recently: |
| type: boolean |
| restriction_active: |
| type: boolean |
| available_resources: |
| type: integer |
| description: "Resource units remaining this turn" |
| current_step: |
| type: integer |
| max_steps: |
| type: integer |
| done: |
| type: boolean |
| reward: |
| type: number |
| nullable: true |
| data_lag_days: |
| type: integer |
| description: "Reporting lag in days (0 = real-time, 3 = hard task)" |
| message: |
| type: string |
| nullable: true |
|
|
| tasks: |
| - name: easy |
| description: "2 districts, 1 outbreak seeded in D1, real-time data" |
| max_steps: 10 |
| num_districts: 2 |
|
|
| - name: medium |
| description: "4 districts, 2 simultaneous outbreaks, limited resources" |
| max_steps: 15 |
| num_districts: 4 |
|
|
| - name: hard |
| description: "6 districts, 3-day data lag, scarce resources" |
| max_steps: 15 |
| num_districts: 6 |
|
|
| tags: |
| - reinforcement-learning |
| - resource-allocation |
| - sequential-decision-making |
| - epidemic-containment |
| - cascade-dynamics |
| - partial-observability |
| - openenv |
|
|
