Abstract
Numerous studies have developed and analysed strategies for maximising utility in social dilemmas from both an individual agent’s perspective and more generally from the viewpoint of a society. In this paper we bring this body of work together by investigating the success of a wide range of strategies in environments with varying characteristics, comparing their success. In particular we study within agent-based simulations, different interaction topologies, agents with and without mobility, and strategies with and without adaptation in the form of reinforcement learning, in both competitive and cooperative settings represented by the Prisoner’s Dilemma and the Stag Hunt, respectively. The results of our experiments show that allowing agents mobility decreases the level of cooperation in the society of agents, due to singular interactions with individual opponents that limit the possibility for direct reciprocity. Unstructured environments similarly support a greater number of singular interactions and thus higher levels of defection in the Prisoner’s Dilemma. In the Stag Hunt, strategies that prioritise risk taking show a greater level of success regardless of environment topology. Our range of experiments yield new insights into the role that mobility and interaction topologies play in the study of cooperation in agent societies.
Highlights
The extensive work on social dilemmas with self-interested agents has focused mainly on agents whose opponents are in an unchanging set, often represented as nodes in a network
The level of cooperation is given as a percentage where 100% represents that every outcome was mutual cooperation for that particular run
To analyse hypothesis hypothesis 2 (H2) and hypothesis 3 (H3) we look at Figure 4 which shows the average score of the society of agents in the Prisoner’s Dilemma and the Stag Hunt, for each environment
Summary
The extensive work on social dilemmas with self-interested agents has focused mainly on agents whose opponents are in an unchanging set, often represented as nodes in a network. The performance of an agent or a society will be measured by the level of cooperation and the overall payoff achieved Our study uses both the Prisoner’s Dilemma and the Stag Hunt games. In both these social dilemmas two players have the choice of cooperation or defection. The Stag Hunt (Skyrms, 2004) reduces the incentive to defect below the payoff that an agent would get for mutual cooperation, leading to two pure strategy Nash Equilibria. These are mutual cooperation and mutual defection. When the agent chooses to defect there is no chance of the agent losing its payoff, it will have given up the chance for the highest payoff, making this the risk-dominant strategy
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