Necrotic Behavioral Control of Agent Behavior in the Iterated Prisoner’s Dilemma

Saunders, Amanda; Ashlock, Daniel; Greensmith, Julie

Abstract

As the Covid-19 pandemic of 2020 illustrates, controlling the behavior of social agents is a difficult problem. This study examines the potential for an immune-inspired technique called necrosis to steer the behavior of agent populations that are evolving to play the iterated version of the game prisoner's dilemma. A key factor in this is detection of behavioral types. The use of a previously developed technique for fingerprinting the behavior of game playing agents, even complex ones, permits the modelling of control strategies with necrotic behavioral control (NBC). NBC consists of reducing the fitness of agents engaging in an unacceptable behavior. The impact of applying necrosis to a number of agent behaviors is investigated. The strategies always-defect, always-cooperate, and tit-for-two-tats are used as the foci for behavior control by zeroing out the fitness of agents whose behavior is similar to those agents. Our experiments demonstrate that NBC changes the distribution of prisoner's dilemma strategies that arise both when the focal strategy is changed and when the similarity radius used to zero out agent fitness is changed. Filtration focused on the strategy tit-for-two-tats has the largest impact on the evolution of prisoner's dilemma strategies while always cooperate is found to have the least.

Citation

Saunders, A., Ashlock, D., & Greensmith, J. (2021, June). Necrotic Behavioral Control of Agent Behavior in the Iterated Prisoner’s Dilemma. Presented at 2021 IEEE Congress on Evolutionary Computation (CEC), Kraków, Poland

• Presentation Conference Type: Edited Proceedings
• Conference Name: 2021 IEEE Congress on Evolutionary Computation (CEC)
• Start Date: Jun 28, 2021
• End Date: Jul 1, 2021
• Acceptance Date: May 5, 2021
• Online Publication Date: Aug 9, 2021
• Publication Date: Jun 28, 2021
• Deposit Date: Mar 3, 2025
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 1593-1600
• DOI: https://doi.org/10.1109/cec45853.2021.9504866
• Public URL: https://nottingham-repository.worktribe.com/output/10072094
• Publisher URL: https://ieeexplore.ieee.org/document/9504866