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a72a5e3 | 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 | name: negotiation-env
version: "1.0.0"
description: >
Strategic Negotiation Simulation Environment where an AI agent learns
to negotiate under uncertainty with different opponent personalities.
The agent must maximize profit through multi-round price negotiation
while adapting to greedy, fair, or impatient opponents.
author: Team MEta_ai
license: Apache-2.0
environment:
type: simulation
domain: negotiation
real_world_task: automated marketplace pricing and negotiation
observation_space:
type: object
fields:
current_offer:
type: integer
description: Current price on the table
range: [100, 1000]
round:
type: integer
description: Current round number
range: [0, 20]
max_rounds:
type: integer
description: Maximum allowed rounds
role:
type: string
enum: ["buyer", "seller"]
description: Agent's role in the negotiation
last_opponent_action:
type: string
enum: ["START", "OFFER", "ACCEPT"]
description: Opponent's last action
last_opponent_offer:
type: integer
description: Opponent's last offered price
range: [100, 1000]
history:
type: array
description: History of all actions this episode
action_space:
type: object
fields:
action_type:
type: string
enum: ["OFFER", "ACCEPT", "REJECT"]
description: Type of negotiation action
price:
type: integer
description: Price for OFFER actions (ignored for ACCEPT/REJECT)
range: [100, 1000]
reward:
type: float
range: [-50.0, 855.0]
description: >
Reward based on deal profit scaled by time factor.
Partial progress signals during intermediate steps.
Penalty for failed negotiations (-50), bad deals (-20),
and aggressive offers (cumulative -2 per aggressive step).
tasks:
- name: task_a_easy
difficulty: easy
description: Fair opponent, wide ZOPA, 20 rounds
success_threshold: 0.2
- name: task_b_medium
difficulty: medium
description: Greedy opponent, narrow ZOPA, 15 rounds
success_threshold: 0.3
- name: task_c_hard
difficulty: hard
description: Impatient opponent, tight margins, 6 rounds
success_threshold: 0.4
inference:
script: inference.py
env_vars:
- API_BASE_URL
- MODEL_NAME
- HF_TOKEN
deployment:
dockerfile: Dockerfile
platform: huggingface-spaces
tag: openenv
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