File size: 2,612 Bytes
1c03487 0092607 1c03487 b43f9e6 1c03487 0092607 1c03487 14e1e76 1c03487 0092607 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 | 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
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