Phil 1.16.2018

ASRC MKT 7:00 – 4:30

  • Tit for tat in heterogeneous populations
    • The “iterated prisoner’s dilemma” is now the orthodox paradigm for the evolution of cooperation among selfish individuals. This viewpoint is strongly supported by Axelrod’s computer tournaments, where ‘tit for tat’ (TFT) finished first. This has stimulated interest in the role of reciprocity in biological societies. Most theoretical investigations, however, assumed homogeneous populations (the setting for evolutionary stable strategies) and programs immune to errors. Here we try to come closer to the biological situation by following a program that takes stochasticities into account and investigates representative samples. We find that a small fraction of TFT players is essential for the emergence of reciprocation in a heterogeneous population, but only paves the way for a more generous strategy. TFT is the pivot, rather than the aim, of an evolution towards cooperation.
    • It’s a Nature Note, so a quick read. In this case, the transition is from AllD->TFT->GTFT, where evolution stops.
  • A strategy of win-stay, lose-shift that outperforms tit-for-tat in the Prisoner’s Dilemma game
    • The Prisoner’s Dilemma is the leading metaphor for the evolution of cooperative behaviour in populations of selfish agents, especially since the well-known computer tournaments of Axelrod and their application to biological communities. In Axelrod’s simulations, the simple strategy tit-for-tat did outstandingly well and subsequently became the major paradigm for reciprocal altruism. Here we present extended evolutionary simulations of heterogeneous ensembles of probabilistic strategies including mutation and selection, and report the unexpected success of another protagonist: Pavlov. This strategy is as simple as tit-for-tat and embodies the fundamental behavioural mechanism win-stay, lose-shift, which seems to be a widespread rule. Pavlov’s success is based on two important advantages over tit-for-tat: it can correct occasional mistakes and exploit unconditional cooperators. This second feature prevents Pavlov populations from being undermined by unconditional cooperators, which in turn invite defectors. Pavlov seems to be more robust than tit-for-tat, suggesting that cooperative behaviour in natural situations may often be based on win-stay, lose-shift.
    • win-stay = exploit, lose-shift = explore
  • Five rules for the evolution of cooperation
    • Cooperation is needed for evolution to construct new levels of organization. The emergence of genomes, cells, multi-cellular organisms, social insects and human society are all based on cooperation. Cooperation means that selfish replicators forgo some of their reproductive potential to help one another. But natural selection implies competition and therefore opposes cooperation unless a specific mechanism is at work. Here I discuss five mechanisms for the evolution of cooperation: kin selection, direct reciprocity, indirect reciprocity, network reciprocity and group selection. For each mechanism, a simple rule is derived which specifies whether natural selection can lead to cooperation.
  • Added a paragraph to the previous work section to include Tit-for-Tat and Milti-armed Bandit previous work.
  • Worked with Aaron on setting up sprint goals