Evolutionary prisoner's dilemma on evolving random networks

The impact of dynamic linking on cooperation on complex networks

In complex social systems, individual relationships and the surrounding environment are constantly changing, allowing individuals to interact on dynamic networks. This study aims to investigate how individuals in a dynamic network engaged in a prisoner's dilemma game adapt their competitive environment through random edge breaks and reconnections when faced with incomplete information and adverse local conditions, thereby influencing the evolution of cooperative behavior. We find that random edge breaks and reconnections in dynamic networks can disrupt cooperative clusters, significantly hindering the development of cooperation. This negative impact becomes more pronounced over larger time scales. However, we also observe that nodes with higher degrees of connectivity exhibit greater resilience to this cooperation disruption. Our research reveals the profound impact of dynamic network structures on the evolution of cooperation and provides new insights into the mechanisms of cooperation in complex systems.

The role of memory in human strategy updating in optional public goods game

Most research suggests that humans can optimize their behavior by imitating other humans. However, it remains unclear whether humans actually imitate others in real-life situations. To address this question, we conducted spatial public goods experiments with voluntary participation. In direct contrast to the prevailing view, the results of our experiments show that imitation plays an insignificant role in the decision making process. Furthermore, we found that the nature of human decision making relied more on their performances in the game's earlier history rather than the performance they observed in others. The action that gained better results in one's own history had a higher chance to be adopted even if this action did not work for the others.

Biological trade and markets

Cooperation between organisms can often be understood, like trade between merchants, as a mutually beneficial exchange of services, resources or other 'commodities'. Mutual benefits alone, however, are not sufficient to explain the evolution of trade-based cooperation. First, organisms may reject a particular trade if another partner offers a better deal. Second, while human trade often entails binding contracts, non-human trade requires unwritten 'terms of contract' that 'self-stabilize' trade and prevent cheating even if all traders strive to maximize fitness. Whenever trading partners can be chosen, market-like situations arise in nature that biologists studying cooperation need to account for. The mere possibility of exerting partner choice stabilizes many forms of otherwise cheatable trade, induces competition, facilitates the evolution of specialization and often leads to intricate forms of cooperation. We discuss selected examples to illustrate these general points and review basic conceptual approaches that are important in the theory of biological trade and markets. Comparing these approaches with theory in economics, it turns out that conventional models-often called 'Walrasian' markets-are of limited relevance to biology. In contrast, early approaches to trade and markets, as found in the works of Ricardo and Cournot, contain elements of thought that have inspired useful models in biology. For example, the concept of comparative advantage has biological applications in trade, signalling and ecological competition. We also see convergence between post-Walrasian economics and biological markets. For example, both economists and biologists are studying 'principal-agent' problems with principals offering jobs to agents without being sure that the agents will do a proper job. Finally, we show that mating markets have many peculiarities not shared with conventional economic markets. Ideas from economics are useful for biologists studying cooperation but need to be taken with caution.