Inter-role reciprocity in evolutionary trust game on square lattices.

Area of Science:

• Computational game theory
• Agent-based modeling
• Evolutionary game theory

Background:

• Simulating bipartite games, such as the trust game, presents challenges in distinguishing roles within a single population.
• Existing models often lack a natural mechanism for role differentiation, hindering the study of inter-role dynamics.

Purpose of the Study:

• To propose a novel simulation framework for bipartite games using a square lattice topology.
• To investigate the emergence of trust through inter-role spatial reciprocity in agent-based simulations.
• To identify optimal conditions for trust emergence based on return ratios.

Main Methods:

• Utilizing a square lattice topology with alternating trustors and trustees to create distinct sub-lattices for learning and interaction.
• Implementing agent-based simulations on this spatial structure to model game dynamics.
• Analyzing the impact of varying return ratios on the formation of inter-role clusters and the survival of agents.

Main Results:

• Detection of an inter-role spatial reciprocity mechanism facilitating trust emergence.
• Identification of a moderate return ratio as crucial for forming inter-role clusters and promoting trust.
• Demonstration that extreme return ratios (too high or too low) negatively impact either trustees or trustors, respectively.

Conclusions:

• The proposed square lattice framework effectively simulates bipartite games and reveals mechanisms for trust emergence.
• Inter-role spatial reciprocity, driven by a moderate return ratio, is key to fostering cooperation in trust games.
• The simulation framework is adaptable for studying various bipartite games and their spatial mechanisms.