Complexity Control in Artificial Self-Organizing Systems: The Case of Bottom-Up versus Top-Down Intervention When
Korosh Mahmoodi1, James K Hazy2
1University of North Texas, Denton.
Nonlinear Dynamics, Psychology, and Life Sciences
|January 4, 2025
Summary
Selfish algorithm agents (SA-agents) in a prisoner's dilemma simulation exhibit emergent intelligence and collective agency. These adaptive systems demonstrated resilience against an artificial virus, comparing top-down and bottom-up control strategies.
Area of Science:
- Complex systems
- Agent-based modeling
- Computational social science
Background:
- Agent-based modeling (ABM) is crucial for simulating complex systems.
- Selfish algorithm agents (SA-agents) offer a framework for studying emergent behaviors.
- The prisoner's dilemma game models strategic interactions and cooperation.
Purpose of the Study:
- To model an adaptive agent-based environment using SA-agents in a multi-round prisoner's dilemma game.
- To investigate emergent intelligence and collective agency in SA-agent interactions.
- To assess the adaptability of the collective network in response to environmental changes, specifically viral contagion.
Main Methods:
- Utilized selfish algorithm agents (SA-agents) within an agent-based environment.
- Simulated multi-round prisoner's dilemma games to observe agent interactions and network dynamics.
- Introduced an artificial virus to test the collective's adaptability and resilience, comparing top-down and bottom-up control strategies.
Main Results:
- Observed emergent intelligence and collective agency as properties of the SA-agent collective.
- Demonstrated the collective's ability to reorganize its network structure in response to changing environmental conditions (viral spread).
- Analyzed the impact of viral contagion on collective reward-seeking performance and compared the efficacy of different control strategies.
Conclusions:
- SA-agent models can exhibit emergent intelligence and collective agency, mirroring properties of living systems.
- The adaptive nature of the collective allows for network reorganization to maintain performance under stress.
- Both exogenous top-down and endogenous bottom-up self-isolation strategies can be employed to manage contagion within the collective.
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