Computational Model Library

Displaying 4 of 4 results spatial prisoner's dilemma clear

Stochastic vs. Deterministic Spatial PD

Andrew Bausch | Published Friday, November 01, 2013 | Last modified Monday, April 08, 2019

This model implements a Spatial Prisoner’s Dilemma with the option to change whether agents interact deterministically or stochastically.

Previous work with the spatial iterated prisoner’s dilemma has shown that “walk away” cooperators are able to outcompete defectors as well as cooperators that do not respond to defection, but it remains to be seen just how robust the so-called walk away strategy is to ecologically important variables such as population density, error, and offspring dispersal. Our simulation experiments identify socio-ecological conditions in which natural selection favors strategies that emphasize forgiveness over flight in the spatial iterated prisoner’s dilemma. Our interesting results are best explained by considering how population density, error, and offspring dispersal affect the opportunity cost associated with walking away from an error-prone partner.

Spatial model of the noisy Prisoner's Dilemma with reward shift

Matus Halas | Published Thursday, March 05, 2015 | Last modified Tuesday, May 29, 2018

Interactions of players embedded in a closed square lattice are determined by distance and overall gains and they lead to shifts of reward payoff between temptation and punishment. A new winner balancing against threats is ultimately discovered.

An agent-based model to study the effects of trust in coalition formation

Luis Nardin | Published Wednesday, August 31, 2011 | Last modified Saturday, April 27, 2013

This model is an agent-based simulation that consists of agents who play the spatial prisioner’s dilemma game with coalition formation. The coalition dynamics are mainly influenced by how much the agents trust their leaders. The main objective is provide a simulation model to enable the analysis of the impacts that the use of trust may cause in coalition formation.

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