A cognitive model of dynamic cooperation with varied interdependency information

Area of Science:

• Cognitive Science
• Game Theory
• Behavioral Economics

Background:

• The Prisoner's Dilemma (PD) is a fundamental model for studying cooperation and defection in strategic interactions.
• Understanding how players adapt their strategies based on interdependency information is crucial for explaining emergent cooperation.

Purpose of the Study:

• To analyze the dynamics of repeated interactions in the Prisoner's Dilemma.
• To propose and test an instance-based learning cognitive model (IBL-PD) for cooperation.
• To evaluate six hypotheses on how players account for opponent outcomes.

Main Methods:

• Simulated repeated Prisoner's Dilemma games with varying levels of interdependency information.
• Testing six distinct hypotheses: selfish, extreme fairness, moderate fairness, linear increasing, hyperbolic discounting, and dynamic expectations.
• Comparing model predictions against empirical data under different information conditions.

Main Results:

• When players lack explicit opponent feedback, behavior aligns with the selfish hypothesis.
• With explicit opponent feedback, the dynamic expectations hypothesis provides the most accurate predictions.
• The instance-based learning cognitive model (IBL-PD) effectively captures the emergence of cooperation.

Conclusions:

• Player behavior in the Prisoner's Dilemma is sensitive to the availability of interdependency information.
• Dynamic expectations, which adjust based on prediction errors, are key to explaining cooperation when feedback is provided.
• The IBL-PD model offers a robust framework for understanding adaptive strategies in repeated social dilemmas.