Troy Siemers’s scientific contributions

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Publications (2)

Hardwired initial conditions.
Case p = 0.2, V ranging [5 10 25 40 60]. Here y* = 0.385 and x* ranging [−0.154, 0, 0.092, 0.115, 0.128].
Case p = 0.4, V ranging [5 10 25 40 60]. Here y* = 0.454 and x* ranging [0, 0.18, 0.29, 0.318, 0.33].
Case p = 0.6, V ranging [5 10 25 40 60]. Here y* = 0.556 and x* ranging [0.22, 0.44, 0.58, 0.61, 0.63].
Case p = 0.8, V ranging [5 10 25 40 60]. Here y* = 0.71 and x* ranging [0.57, 0.86, 1.03, 1.07, 1.09].

+4

Political Competition, Resource Availability, and Conflict: A Simulation
  • Article
  • Full-text available

February 2025

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17 Reads

Troy Siemers

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Atin Basuchoudhary

This paper explores the dynamics of political competition, resource availability, and conflict through a simulation-based approach. Utilizing agent-based models (ABMs) within an evolutionary game theoretical framework, we investigate how individual behaviors and motivations influence collective outcomes in civil conflicts. Our study builds on the theoretical model developed by Basuchoudhary et al. (2023), which integrates factors such as resource availability, state capacity, and political entrepreneurship to explain the evolution of civil conflict. By simulating boundedly rational agents, we demonstrate how changes in resource availability can alter the nature of civil conflict, leading to different equilibrium outcomes. The findings highlight the importance of understanding individual motivations and adaptive behaviors in predicting the stability and resolution of conflicts. This research contributes to the growing body of literature on the use of agent-based models in evolutionary game theory and provides valuable insights into the complex interactions that drive civil violence.

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Figure 1. A representative phase diagram when L> α.
Figure 3. Case p = 0.2, V ranging [5 10 25 40 60]. Here y* = 0.385 and x* ranging [-0.154,0,0.092,0.115,0.128]
Figure 4. Case p = 0.4, V ranging [5 10 25 40 60]. Here y* = 0.454 and x* ranging [0,0.18,0.29,0.318,0.33]
Figure 5. Case p = 0.6, V ranging [5 10 25 40 60]. Here y* = 0.556 and x* ranging [0.22,0.44,0.58,0.61,0.63]
Figure 6. Case p = 0.8, V ranging [5 10 25 40 60]. Here y* = 0.71 and x* ranging [0.57,0.86,1.03,1.07,1.09] Scenario 2. L < α

+2

Political Competition, Resource Availability, and Conflict: A Simulation

September 2024

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25 Reads

Troy Siemers

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James Hentz

This paper explores the dynamics of political competition, resource availability, and conflict through a simulation-based approach. Utilizing agent-based models (ABMs) within an evolutionary game theoretical framework, we investigate how individual behaviors and motivations influence collective outcomes in civil conflicts. Our study builds on the theoretical model developed by Basuchoudhary et al. (2023), which integrates factors such as resource availability, state capacity, and political entrepreneurship to explain the evolution of civil conflict. By simulating boundedly rational agents, we demonstrate how changes in resource availability and state capacity can alter the nature of civil conflict, leading to different equilibrium outcomes. The findings highlight the importance of understanding individual motivations and adaptive behaviors in predicting the stability and resolution of conflicts. This research contributes to the growing body of literature on the use of agent-based models in evolutionary game theory and provides valuable insights into the complex interactions that drive civil violence.

Download