Just How (Un)realistic are Evolutionary Algorithms as Representations of Social Processes

TLDR: This paper summarises and draws out the implications of the Neo-Darwinian Synthesis for processes of social evolution and discusses the extent to which evolutionary algorithms capture the aspects of biological evolution which are relevant to social processes.

Abstract: This paper attempts to illustrate the importance of a coherent behavioural interpretation in applying evolutionary algorithms like Genetic Algorithms and Genetic Programming to the modelling of social processes. It summarises and draws out the implications of the Neo-Darwinian Synthesis for processes of social evolution and then discusses the extent to which evolutionary algorithms capture the aspects of biological evolution which are relevant to social processes. The paper uses several recent papers in the field as case studies, discussing more and less successful uses of evolutionary algorithms in social science. The key aspects of evolution discussed in the paper are that it is dependent on relative rather than absolute fitness, it does not require global knowledge or a system level teleology, it avoids the credit assignment problem, it does not exclude Lamarckian inheritance and it is both progressive and open ended.