Inductive Game Theory and the Dynamics of Animal Conflict

Abstract

Conflict destabilizes social interactions and impedes cooperation at multiple scales of biological organization. Of fundamental interest are the causes of turbulent periods of conflict. We analyze conflict dynamics in a monkey society model system. We develop a technique, Inductive Game Theory, to extract directly from time-series data the decision-making strategies used by individuals and groups. This technique uses Monte Carlo simulation to test alternative causal models of conflict dynamics. We find individuals base their decision to fight on memory of social factors, not on short timescale ecological resource competition. Furthermore, the social assessments on which these decisions are based are triadic (self in relation to another pair of individuals), not pairwise. We show that this triadic decision making causes long conflict cascades and that there is a high population cost of the large fights associated with these cascades. These results suggest that individual agency has been over-emphasized in the social evolution of complex aggregates, and that pair-wise formalisms are inadequate. An appreciation of the empirical foundations of the collective dynamics of conflict is a crucial step towards its effective management.

arXiv comment37 pages, includes Supplementary Information, matches PLoS version

References in corpus (4)

• Weak pairwise correlations imply strongly correlated network states in a neural population
• Measuring the effective complexity of cosmological models
• Ising models for networks of real neurons
• Physics and Complexity

Cited by in corpus (10)

• Control of critical behavior in a small-scale social system
• Collective Phenomena and Non-Finite State Computation in a Human Social System
• Dynamical Structure of a Traditional Amazonian Social Network
• Dynamics and Processing in Finite Self-Similar Networks
• Evidence of strategic periodicities in collective conflict dynamics
• Major Transitions in Political Order
• Group Minds and the Case of Wikipedia
• Conflict and Computation on Wikipedia: a Finite-State Machine Analysis of Editor Interactions
• Evolutionary model discovery of causal factors behind the socio-agricultural behavior of the ancestral Pueblo
• Evolution of cooperation in multi-agent systems with time-varying tags, multiple strategies, and heterogeneous invasion dynamics