Catalytic evolution of cooperation in a population with behavioural bimodality

Abstract

The remarkable adaptability of humans in response to complex environments is often demonstrated by the context-dependent adoption of different behavioral modes. However, the existing game-theoretic studies mostly focus on the single-mode assumption, and the impact of this behavioral multimodality on the evolution of cooperation remains largely unknown. Here, we study how cooperation evolves in a population with two behavioral modes. Specifically, we incorporate Q-learning and Tit-for-Tat (TFT) rules into our toy model, where prisoner's dilemma game is played and we investigate the impact of the mode mixture on the evolution of cooperation. While players in Q-learning mode aim to maximize their accumulated payoffs, players within TFT mode repeat what their neighbors have done to them. In a structured mixing implementation where the updating rule is fixed for each individual, we find that the mode mixture greatly promotes the overall cooperation prevalence. The promotion is even more significant in the probabilistic mixing, where players randomly select one of the two rules at each step. Finally, this promotion is robust when players are allowed to adaptively choose the two modes by real-time comparison. In all three scenarios, players within the Q-learning mode act as catalyzer that turns the TFT players to be more cooperative, and as a result drive the whole population to be highly cooperative. The analysis of Q-tables explains the underlying mechanism of cooperation promotion, which captures the ``psychologic evolution" in the players' mind. Our study indicates that the variety of behavioral modes is non-negligible, and could be crucial to clarify the emergence of cooperation in the real world.

11 pages, 12 figure. Comments are appreciated

References in corpus (19)

• Evolutionary games on graphs
• Statistical physics of human cooperation
• Social diversity and promotion of cooperation in the spatial prisoner's dilemma game
• Interdependent network reciprocity in evolutionary games
• Human strategy updating in evolutionary games
• Mathematical foundations of moral preferences
• Conformity enhances network reciprocity in evolutionary social dilemmas
• Heterogeneous update mechanisms in evolutionary games: mixing innovative and imitative dynamics
• Competition and partnership between conformity and payoff-based imitations in social dilemmas
• Evolution of cooperation driven by zealots
• Artificial intelligence meets minority game: toward optimal resource allocation
• Emergence of Cooperation in Two-agent Repeated Games with Reinforcement Learning
• Decoding trust: A reinforcement learning perspective
• Dynamical reciprocity in interacting games: numerical results and mechanism analysis
• Emergence of anti-coordinated patterns in snowdrift game by reinforcement learning
• Emergence of cooperation in a population with bimodal response behaviors
• Social hierarchy promotes the cooperation prevalence
• Optimal coordination of resources: A solution from reinforcement learning
• Probabilistic fair behaviors spark its boost in the Ultimatum Game: the strength of good Samaritans

Cited by in corpus (2)

• Evolution of cooperation with Q-learning: the impact of information perception
• Evolution of cooperation in a bimodal mixture of conditional cooperators