| ---
|
| license: cc-by-4.0
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| task_categories:
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| - reinforcement-learning
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| - tabular-classification
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| language:
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| - en
|
| tags:
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| - synthetic
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| - finance
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| - defi
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| - crypto
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| - mcts
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| - trading-agents
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| - execution-intelligence
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| pretty_name: Solstice ARC-T DeFi Execution Intelligence
|
| ---
|
|
|
| # Solstice ARC-T DeFi Execution Intelligence (Sample)
|
|
|
| **Synthetic risk-to-execution decision loops for autonomous DeFi agents.** This dataset captures 3,000 multi-step decision traces from autonomous trading agents operating in a simulated Decentralized Finance (DeFi) ecosystem.
|
|
|
| Built by [Solstice AI Studio](https://www.solsticestudio.ai/datasets) as a free sample of a larger commercial pack. 100% synthetic — no real wallet addresses or on-chain history used.
|
|
|
| ## What's in the box
|
| Each record in the JSONL stream represents a full execution loop, including:
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| - **Market State:** Simulated oracle prices, liquidity depths, and volatility triggers.
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| - **Risk Assessment:** Whale movement signals and oracle staleness metrics.
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| - **Agent Reasoning:** MCTS-style strategy selection (Monte Carlo Tree Search) with success/failure probability weights.
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| - **Execution Outcome:** Final trade result including gas costs, slippage, and PnL.
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|
|
| ## Use Cases
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| - **Autonomous Agent Training:** Train models to select optimal trading strategies based on simulated market stress.
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| - **Risk Model Evaluation:** Benchmark protocol safety against extreme market scenarios and oracle failures.
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| - **Anomaly Detection:** Identify malicious or inefficient trading patterns in high-frequency DeFi telemetry.
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|
|
| ## Data Provenance
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| Generated using Solstice’s PhantasOS / SIMA simulation engine. The simulation uses MCTS (Monte Carlo Tree Search) to explore the decision space of a trading agent, recording both the chosen path and the explored alternatives.
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|
|
| ## Get the Full Pack
|
| Scale this dataset to 1M+ decision loops, including cross-chain bridge logic and complex liquidity provider (LP) scenarios.
|
| [www.solsticestudio.ai/datasets](https://www.solsticestudio.ai/datasets)
|
|
|
