A Co-evolutionary Simulation of Multi-Branch Enterprises
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Transcript of A Co-evolutionary Simulation of Multi-Branch Enterprises
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A Co-evolutionary Simulation
of Multi-Branch Enterprises
Edmund ChattoeCentre for Research on Simulation in the Social
Sciences (CRESS),Department of Sociology
University of SurreyGuildford GU2 5XH
[email protected]://www.soc.surrey.ac.uk/staff/edmund_chattoe.html
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Simulation
• Social processes as computer programs.
• Heterogeneous agents: firms, branches and consumers.
• Parallel autonomous processes.• Linking macro/micro and
mental state/action.• Integration of theories.• Integration of data: qualitative
and quantitative.
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Evolutionary Approaches to Social Action
• Not genetic determinism!• Population Approach: Mental
models leading to actions with differential success.
• Distinction between agent and environment.
• Robust self-organisation with minimal rationality.
• Concrete models based on Evolutionary Algorithms.
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Motivation of the Model
• Suitable market for evolutionary modelling.
• Intuitive environment for fair comparison of learning methods.
• Difficult learning task.• “Independent” specification of
agents in simulation.• Possibilities for emergent data.• High level view of relation
between agents and environment.
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High Level Description
• Spatially distributed consumers and branches.
• Consumers seek suitable meals.• Firms collect sales/practice data.• Learning changes practices.• Consumers, branches and firms
linked by common representation of practices:
0000010010110
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Consumers
• Fixed chance of hunger.• Two behaviour modes (random
search and loyalty) and memory of “best” branch.
• Tolerance based on Hamming Distance.
• Changing tolerance.• Fatigue.• Consumer types.• Dis-satisfaction.
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Firms and Branches
• Set of practices.• Running and capital costs.• Income from sales.• Profits as surplus over costs.• Learning algorithm and
decision process.
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Consumer Conditions
• Random practice change on loss.• Fixed preference, no tolerance, 4
types.• Fixed preference, tolerance 1, 4
types.• Changing preference, no
tolerance, 4 types.• No tolerance, fatigue, 4 types.• Fixed preference, tolerance 1, no
types.
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Learning Conditions
• No adaptation.• Random change on loss.• Independent hill-climbing.• Loss threshold leading to
imitation/Lamarckian differentiation.
• Many more possibilities ...
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Results: Learning Conditions
Run Total Sales Dis-satisfaction Total ProfitsReference 6,689 213,439 12,155Reference 8,977 114,434 27,004Condition 6 4,321 317,728 -8,084Condition 6 5,964 245,496 -9,104Condition 7 7,123 195,608 929Condition 7 7,712 165,594 22,641Condition 8 7,588 172,319 19,893Condition 8 9,886 75,566 45,211
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Discussion
• Profit insulates from selection.• Satisficing is environmentally
stable while optimising is not.• Need to identify market niches
based on consumer knowledge.• Hill-climbing has difficulties in
non-stationary environments.• Even naive evolution is
surprisingly effective.
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IMAGES Project
• Payments for ecological activities.• Agent based models of innovation
diffusion.• Information transfer through
social networks.• Interaction of social and economic
reasoning.• Integration of qualitative
interviews, farm surveys and secondary data.
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Modelling Budgetary Decision of Pensioners
• Developing simulation inductively from interviews.
• Integrating economic and sociological theories.
• Importance of:o Time planning.o Durable scheduling.o Joint activities.o Budgeting strategies: multiple accounts.
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Evolution of Pricing Strategies in Oligopoly
• Firms use Genetic Programs to set prices.
• Programs are modified by profit induced mutation/imitation.
• Random generation of strategies still allows stable markets and responsive behaviour.
• Stylised behaviours like price following and “cost plus” pricing are observed to evolve.
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Research Plans
o Simulations linking actual firm micro practices with market outcomes.
o Extension of time planning approach beyond consumption choice.
o Memetic models of information transmission for establishment of “culture”.
o Social dimensions of electronic commerce and crime.
o Agent based models of innovation diffusion: a case based approach.
o Charity shops as alternative spaces of consumption.