# Stake Chess: LLM-Guided RL Training for Human Tendency Exploitation

- **Event:** [WeaveHacks 3: Self-Improving Agents Hackathon with Weights & Biases](https://cerebralvalley.ai/e/weave-hacks-3-self-improving-agents-hackathon-with-weights-and-biases-7014fe80)
- **When:** Jan 31 at 9:00 AM – Feb 1 at 5:00 PM (PST)
- **Where:** 400 California St, San Francisco, CA
- **Team:** [aTG R](https://cerebralvalley.ai/u/atg), [Daniil Kardava](https://cerebralvalley.ai/u/daniil), [Azeem Muhammad](https://cerebralvalley.ai/u/zxaletter)
- **GitHub:** https://github.com/r-agni/llmguidedRLTraining
- **Demo video:** https://drive.google.com/drive/folders/1Txi-Lw684RjZTaqv2y8jfc89EvTKAN8B?usp=sharing
- **Gallery:** https://cerebralvalley.ai/e/weave-hacks-3-self-improving-agents-hackathon-with-weights-and-biases-7014fe80/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/weave-hacks-3-self-improving-agents-hackathon-with-weights-and-biases-7014fe80/hackathon/gallery/17

We introduce Stake Chess, a novel chess variant that adds hidden information through a biased staking mechanism, reshaping strategic play under uncertainty. The game is paired with an LLM-guided reinforcement learning architecture designed to model human psychological behavior. Using an 8-dimensional player profiling system powered by Qwen-3, our method accelerates convergence toward Nash-equilibrium strategies while outperforming human opponents. The approach show promise compared to traditional self-play methods and is grounded in game-theoretic analysis.

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Markdown version of https://cerebralvalley.ai/e/weave-hacks-3-self-improving-agents-hackathon-with-weights-and-biases-7014fe80/hackathon/gallery/17. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt