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T Killingback

Publications and source records attributed to T Killingback.

5 recordsLinked to original sources

Spatial Ultimatum Games, collaborations and the evolution of fairness.

It is often the case that individuals in a social group can perform certain tasks (such as hunting, for example) more efficiently if they collaborate with other individuals than if they act alone. In such situations one is necessarily faced with the problem of how the resource obtained as the result of such a collaboration should be divided among the collaborating individuals. If one of the individuals in the collaboration is in a position (through its dominance rank, for example) to impose a particular division of the resource on the other members of the collaboration then we show that an evolutionary dilemma arises which prevents such collaborations being evolutionarily stable. This dilemma, which is closely related to the well-known Ultimatum Game, results from the fact that in such situations natural selection favours individuals who, if dominant, offer smaller and smaller shares of the resource to the others and, if subdominant, will accept lower and lower offers. We also show, however, that this dilemma is naturally resolved in a spatially structured population with selection favouring the evolution of a fair division of the resource and consequently ensuring the evolutionary stability of collaborations of this type.

Animals↗

Evolution of cooperation in spatially structured populations

Using a spatial lattice model of the Iterated Prisoner's Dilemma we studied the evolution of cooperation within the strategy space of all stochastic strategies with a memory of one round. Comparing the spatial model with a randomly mixed model showed that (1) there is more cooperative behaviour in a spatially structured population, (2) PAVLOV and generous variants of it are very successful strategies in the spatial context and (3) in spatially structured populations evolution is much less chaotic than in unstructured populations. In spatially structured populations, generous variants of PAVLOV are found to be very successful strategies in playing the Iterated Prisoner's Dilemma. The main weakness of PAVLOV is that it is exploitable by defective strategies. In a spatial context this disadvantage is much less important than the good error correction of PAVLOV, and especially of generous PAVLOV, because in a spatially structured population successful strategies always build clusters. Copyright 1999 Academic Press.

Journal Article↗

Variable investment, the Continuous Prisoner's Dilemma, and the origin of cooperation.

Cooperation is fundamental to many biological systems. A common metaphor for studying the evolution of cooperation is the Prisoner's Dilemma, a game with two strategies: cooperate or defect. However, cooperation is rare all or nothing, and its evolution probably involves the gradual extension of initially modest degrees of assistance. The inability of the Prisoner's Dilemma to capture this basic aspect limits its use for understanding the evolutionary origins of cooperation. Here we consider a framework for cooperation based on the concept of investment: an act which is costly, but which benefits other individuals, where the cost and benefit depend on the level of investment made. In the resulting Continuous Prisoner's Dilemma the essential problem of cooperation remains: in the absence of any additional structure non-zero levels of investment cannot evolve. However, if investments are considered in a spatially structured context, selfish individuals who make arbitrarily low investments can be invaded by higher-investing mutants. This results in the mean level of investment evolving to significant levels, where it is maintained indefinitely. This approach provides a natural solution to the fundamental problem of how cooperation gradually increases from a non-cooperative state.

Biological Evolution↗

Self-organized criticality in spatial evolutionary game theory.

Self-organized criticality is an important framework for understanding the emergence of scale-free natural phenomena. Cellular automata provide simple interesting models in which to study self-organized criticality. We consider the dynamics of a new class of cellular automata which are constructed as natural spatial extensions of evolutionary game theory. This construction yields a discrete one-parameter family of cellular automata. We show that there is a range of parameter values for which this system exhibits complex dynamics with long range correlations between states in both time and space. In this region the dynamics evolve to a self-organized critical state in which structures exist on all time and length scales, and the relevant statistical measures have power law behaviour.

Animals↗