Formal Darwinism, the individual-as-maximizing-agent analogy and bet-hedging

Journal article

The central argument of The origin of species was that mechanical processes (inheritance of features and the differential reproduction they cause) can give rise to the appearance of design. The 'mechanical processes' are now mathematically represented by the dynamic systems of population genetics, and the appearance of design by optimization and game theory in which the individual plays the part of the maximizing agent. Establishing a precise individual-as-maximizing-agent (IMA) analogy for a population genetics system justifies optimization approaches, and so provides a modern formal representation of the core of Darwinism. It is a hitherto unnoticed implication of recent population-genetics models that, contrary to a decades-long consensus, an IMA analogy can be found in models with stochastic environments (subject to a convexity assumption), in which individuals maximize expected reproductive value. The key is that the total reproductive value of a species must be considered as constant, so therefore reproductive value should always be calculated in relative terms. This result removes a major obstacle from the theoretical challenge to find a unifying framework which establishes the IMA analogy for all of Darwinian biology, including as special cases inclusive fitness, evolutionarily stable strategies, evolutionary life-history theory, age-structured models and sex ratio theory. This would provide a formal, mathematical justification of fruitful and widespread but 'intentional' terms in evolutionary biology, such as 'selfish', 'altruism' and 'conflict'.

Authors: Grafen, A

• Publication status: Published
• Journal: PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
• Volume: 266
• Issue: 1421
• Pages: 799-803
• Publication date: 1999-04-22
• DOI: 10.1098/rspb.1999.0708
• EISSN: 1471-2970
• ISSN: 0962-8452
• Language: English
• Keywords: Bet-hedging; Population genetics; Reproductive value; Darwinism; Maximizing agent; Game theory