| Abstrakt: |
Signalling games are popular models for studying the evolution of meaning, but typical approaches do not incorporate vagueness as a feature of successful signalling. Complementing recent like-minded models, we describe an aggregate population-level dynamic that describes a process of imitation of successful behaviour under imprecise perception and realization of similar stimuli. Applying this new dynamic to a generalization of Lewis's signalling games, we show that stochastic imprecision leads to vague, yet by-and-large efficient signal use, and, moreover, that it unifies evolutionary outcomes and helps avoid sub-optimal categorization. The upshot of this is that we see 'as-if'-generalization at an aggregate level, without agents actually generalizing. 1 Introduction 2 Background 2.1 Sim-max games and conceptual spaces 2.2 Vagueness in sim-max games and conceptual spaces 2.3 Vagueness, functional pressure, and transmission biases 3 Imprecise Imitation 3.1 Replicator dynamic in behavioural strategies 3.2 Noise-perturbed conditional imitation 4 Exploring Imprecise Imitation 4.1 Setting the stage 4.2 Simulation set-up 4.3 Measures of interest 4.4 Results 5 Discussion 5.1 Levels of vagueness 5.2 Evolutionary benefits of imprecision 5.3 Related work 6 Conclusion Appendix [ABSTRACT FROM AUTHOR] |
