Two agent-based models of cooperation in dynamic groups and fixed social networks (1.0.0)
            Both models simulate n-person prisoner dilemma in groups (left figure) where agents decide to C/D – using a stochastic threshold algorithm with reinforcement learning components. We model fixed (single group ABM) and dynamic groups (bad-barrels ABM). The purpose of the bad-barrels model is to assess the impact of information during meritocratic matching. In the bad-barrels model, we incorporated a multidimensional structure in which agents are also embedded in a social network (2-person PD). We modeled a random and homophilous network via a random spatial graph algorithm (right figure). 
             
            Release Notes
            Version 1.0.0 of June 2021
            Associated Publications
            de Matos Fernandes, C.A., Flache, A., Bakker, D.M., & Dijkstra, J. (2022). A Bad Barrel Spoils a Good Apple: How Uncertainty and Networks Affect Whether Matching Rules Can Foster Cooperation. Journal of Artificial Societies and Social Simulation, 25(1), 6. doi: 10.18564/jasss.4754
         
    
    
        
        
            
        
        Two agent-based models of cooperation in dynamic groups and fixed social networks 1.0.0
        
        
        
            
                Both models simulate n-person prisoner dilemma in groups (left figure) where agents decide to C/D – using a stochastic threshold algorithm with reinforcement learning components. We model fixed (single group ABM) and dynamic groups (bad-barrels ABM). The purpose of the bad-barrels model is to assess the impact of information during meritocratic matching. In the bad-barrels model, we incorporated a multidimensional structure in which agents are also embedded in a social network (2-person PD). We modeled a random and homophilous network via a random spatial graph algorithm (right figure). 
             
            
                
                
                
            
            
            Release Notes
            
                
Version 1.0.0 of June 2021