Entangled and correlated photon mixed strategy for social decision making

Area of Science:

• Quantum Information Science
• Game Theory
• Decision Science

Background:

• Collective decision-making is crucial for resource management and social infrastructure applications.
• The competitive multi-armed bandit (CMAB) problem involves multiple players maximizing rewards from multiple options.
• Previous work showed entangled photons resolve CMAB decision conflicts and ensure equality.

Purpose of the Study:

• To enhance total rewards in CMAB problems beyond entangled-photon-only strategies.
• To investigate a mixed strategy combining entangled and correlated photons.
• To determine if mixed strategies outperform purely entangled photon strategies in CMAB.

Main Methods:

• Developing and analyzing a mixed decision-making strategy using both entangled and correlated photons.
• Experimentally demonstrating the mixed strategy in a CMAB scenario.
• Evaluating the impact of environmental dynamics and problem difficulty on strategy performance.

Main Results:

• The mixed strategy significantly enhances total rewards compared to using only entangled photons.
• An optimal mixture of entangled and correlated photon strategies was identified.
• The effectiveness of the mixture depends on reward environment dynamics and problem complexity.

Conclusions:

• A mixed photon-based strategy offers superior performance in CMAB problems.
• This approach leverages both quantum and classical photon properties for enhanced decision-making.
• Mixed strategies demonstrate supremacy, echoing findings in evolutionary game theory.