菜单
Quenching speculation in markets via entangled neural traders — prototype quantum stock market where entanglement between traders' valuations mitigates speculative busts before they emerge. RL agents with quantum-correlated qubit valuations learn to stabilize markets.
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| name | entangled-neural-trader-market-stabilization |
| description | Quenching speculation in markets via entangled neural traders — prototype quantum stock market where entanglement between traders' valuations mitigates speculative busts before they emerge. RL agents with quantum-correlated qubit valuations learn to stabilize markets. |
A prototype quantum stock market framework where entanglement between traders' valuations mitigates speculative dynamics before they emerge. Uses reinforcement learning agents with quantum-correlated qubit valuations to learn market-stabilizing behaviors. Demonstrates that quantum entanglement can serve as a mechanism to reduce speculative trading instabilities.
Market Environment → Multiple RL Agents
→ Each agent has quantum-correlated qubit valuations
→ Entanglement links agent valuation updates
→ Market price emerges from aggregated actions
→ Feedback loop: price → valuation update → entanglement → action
Trader i valuation: |ψᵢ⟩ = α|buy⟩ + β|sell⟩ + γ|hold⟩
Entanglement: |Ψ⟩ = Σ cᵢⱼ |ψᵢ⟩ ⊗ |ψⱼ⟩
Market price: P = f(Σ action_i)
Speculation damping: D = 1 - |⟨ψᵢ|ψⱼ⟩|² (entanglement measure)