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Self-organized networks of competing boolean agents
1Niels Bohr Institute, Blegdamsvej 17, 2100 Copenhagen, Denmark and NORDITA, Blegdamsvej 17, 2100 Copenhagen, Denmark and Department of Physics, University of Houston, Houston, Texas 77204-5506, USA.
Physical Review Letters
|October 6, 2000
Summary
This study models Boolean agents in a competitive market game. Random strategy mutation in the poorest player leads to intermittent market dynamics and shifts between states.
Area of Science:
- Agent-based modeling
- Market dynamics
- Game theory
Background:
- Complex adaptive systems often exhibit emergent behaviors.
- Understanding market dynamics requires modeling agent interactions and decision-making.
Purpose of the Study:
- To present a model of Boolean agents competing in a market.
- To investigate the long-term dynamics resulting from agent interactions and random strategy mutation.
Main Methods:
- Agent-based modeling of Boolean agents.
- Competitive game simulation rewarding minority strategies.
- Introduction of random mutation for the poorest player's strategy.
- Analysis of network evolution to a stationary, intermittent state.
Main Results:
- The network evolves to a stationary but intermittent state.
- Random mutation of the worst strategy can alter the entire network's behavior.
- The system exhibits switches in dynamics between attractors of varying lengths.
Conclusions:
- Agent-based market models can display complex emergent behaviors.
- Intermittent dynamics and state switching are possible in competitive agent systems.
- Random mutations can act as critical triggers for system-wide behavioral changes.