SKALE Launches Agent Pit, a Simulated Prediction Market Sandbox for Training AI Agents' Trading Strategies
- SKALE Labs has launched Agent Pit, a simulated prediction market sandbox.
- The platform is built on SKALE's zero-gas blockchain.
- Agent Pit replicates Polymarket’s order book and settlement framework.
- Developers can fine-tune AI agents in a risk-free environment.
- Users can compete on a simulated ROI leaderboard before deploying models to real markets.
On August 13, PANews reported that SKALE Labs has launched Agent Pit, a new platform designed for training and testing AI agents' trading strategies. This simulated prediction market sandbox operates on SKALE's zero-gas blockchain, allowing developers to experiment without financial risk.
Agent Pit replicates the order book and settlement framework of Polymarket, providing a familiar environment for users. The platform also includes real-time event data to enhance the training process for AI agents.
Developers and quantitative teams can fine-tune their agents in this risk-free setting and compete on a simulated ROI leaderboard. Once satisfied with their models, they can deploy them to real markets, such as Polymarket, to test their effectiveness in actual trading scenarios.
SKALE推出Agent Pit，一个用于训练AI代理交易策略的模拟预测市场沙盒
8月13日，PANews报道，SKALE Labs推出了Agent Pit，一个旨在训练和测试AI代理交易策略的新平台。该模拟预测市场沙盒在SKALE的零燃气区块链上运行，使开发者能够在没有财务风险的情况下进行实验。
Agent Pit复制了Polymarket的订单簿和结算框架，为用户提供了一个熟悉的环境。该平台还包括实时事件数据，以增强AI代理的训练过程。
开发者和量化团队可以在这个无风险的环境中微调他们的代理，并在模拟的投资回报率排行榜上竞争。一旦对他们的模型感到满意，他们可以将其部署到真实市场，如Polymarket，以测试其在实际交易场景中的有效性。