By Elizabeth Garnsey, James McGlade

Applies principles and strategies from the complexity standpoint to key matters within the social sciences, exploring co-evolutionary procedures.

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Extra info for Complexity And Co-Evolution: Continuity And Change In Socio-Economic Systems

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Ruelle, D. and F. Takens (1971), ‘On the nature of turbulence’, Communications of Mathematical Physics, 20, 167–92. Thom, René (1975), Structural Stability and Morphogenesis, Reading, MA: Benjamin. van der Leeuw, Sander E. (1982), ‘How objective can we become? Some reflections on the nature of the relationship between the archaeologist, his data and his interpretations’, in A. Colin Renfrew, Michael J. Rowlands and Barbara A. Segraves (eds), Theory and Explanation in Archaeology, London: Academic Press, pp.

Because of its differences from x we must assume that it has a different birth rate bЈ and death rate mЈ. If we think about the population dynamics of this small, initial population, then we will now have two logistic equations, one for x and one for xЈ. The ‘crowding term’ expressing the effect of the limiting resource on each of them will also be different, being N for population x, and NЈ for population xЈ. We will now have two equations of population dynamics, one with factors b, m and N and the other with bЈ, mЈ and NЈ.

We can use our model to explore the effect of different learning strategies of firms. The first example will be a kind of Darwinian method called ‘death and replacement’. a. b. c. Death and replacement. In this we assume that firms do not adapt their price and quality strategies but pursue them to success or bankruptcy. Following bankruptcy, however, we re-launch the firms into the system with a new, randomly chosen strategy. This either survives or fails in its turn. The model represents a kind of ‘Darwinian’ model of market evolution in which firms do not learn or change their strategies over time; those random strategies that work remain; and those that don’t are replaced by new, randomly chosen strategies.

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