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| 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 | |