Team decision problems with classical and quantum signals.

Area of Science:

• Game Theory
• Information Economics
• Quantum Information

Background:

• Team decision problems often lack direct communication channels.
• Coordination can be achieved through shared environmental signals.
• Understanding signal types is crucial for optimizing team performance.

Purpose of the Study:

• To analyze team decision problems without communication.
• To investigate the impact of various signal types on team performance.
• To explore the potential of quantum signals in enhancing coordination.

Main Methods:

• Studied team decision problems with varying information structures.
• Examined signal assumptions: perfectly correlated, i.i.d. (independently and identically distributed), exchangeable classical, and quantum signals.
• Analyzed performance in perfect-recall and imperfect-recall trees.

Main Results:

• In perfect-recall trees, no signal type improved performance.
• In imperfect-recall trees, quantum signals showed potential for improvement.
• Classical i.i.d. signals can improve performance in non-Kuhn trees, with further gains from exchangeable or quantum signals.

Conclusions:

• Quantum signals offer a potential advantage in specific team decision scenarios, particularly with imperfect recall.
• The choice of signal type significantly impacts team performance in coordination games.
• Findings have implications for fields like high-frequency trading where rapid, coordinated decisions are vital.