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    <SEQUENTIAL>
      <record key="001" att1="001" value="162740" att2="162740">001   162740</record>
      <field key="037" subkey="x">englisch</field>
      <field key="050" subkey="x">Forschungsbericht</field>
      <field key="076" subkey="">Ökonomie</field>
      <field key="079" subkey="y">http://www.ihs.ac.at/publications/eco/es-190.pdf</field>
      <field key="079" subkey="z">Dorofeenko, Victor - et al., Finite Memory Distributed Systems (pdf)</field>
      <field key="079" subkey="y">http://ideas.repec.org/p/ihs/ihsesp/190.html</field>
      <field key="079" subkey="z">Institute for Advanced Studies. Economics Series; 190 (RePEc)</field>
      <field key="100" subkey="">Dorofeenko, Victor</field>
      <field key="103" subkey="">Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria</field>
      <field key="104" subkey="a">Shorish, Jamsheed</field>
      <field key="107" subkey="">Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria</field>
      <field key="331" subkey="">Finite Memory Distributed Systems</field>
      <field key="403" subkey="">1. Ed.</field>
      <field key="410" subkey="">Wien</field>
      <field key="412" subkey="">Institut für Höhere Studien</field>
      <field key="425" subkey="">2006, May</field>
      <field key="433" subkey="">25 pp.</field>
      <field key="451" subkey="">Institut für Höhere Studien; Reihe Ökonomie; 190</field>
      <field key="451" subkey="h">Kunst, Robert M. (Ed.) ; Fisher, Walter (Assoc. Ed.) ; Ritzberger, Klaus (Assoc. Ed.)</field>
      <field key="461" subkey="">Economics Series</field>
      <field key="517" subkey="c">from the Table of Contents: Introduction; The Model; Model Approximation; Simulations; Conclusion; Appendices;</field>
      <field key="542" subkey="">1605-7996</field>
      <field key="544" subkey="">IHSES 190</field>
      <field key="700" subkey="">C61</field>
      <field key="700" subkey="">C73</field>
      <field key="720" subkey="">Fixed strategy</field>
      <field key="720" subkey="">Prisoner's dilemma</field>
      <field key="720" subkey="">Fokker-Plank</field>
      <field key="720" subkey="">Distributed system</field>
      <field key="750" subkey="h">References: Brock, W.A. and S.N. Durlauf (2002): "A Multinomial Choice Model of Neighborhood Effects," American Economic Review,</field>
      <field key="92," subkey="">298-303 -- Brock, W.A. and S.N. Durlauf (2003): "Multinomial Choice with Social Interactions," NBER Technical Working Paper</field>
      <field key="No." subkey="">288 -- Dorofeenko, V. and J. Shorish (2005): "Partial Differential Equation  Modelling for Stochastic Fixed Strategy</field>
      <field key="Dis" subkey="t">ributed Systems," Journal of Economic  Dynamics and Control, 29(1-2), 335-367 -- Epstein, J. and R. Axtell (1996): Growing</field>
      <field key="Art" subkey="i">ficial Societies. MIT Press -- Epstein, J.M. (1998): "Zones of Cooperation in  Demographic Prisoner's Dilemma," Complexity, 4</field>
      <field key=", 3" subkey="6">-48 -- Kirchkamp, O. (2000): "Spatial  Evolution of Automata in the Prisoners' Dilemma," Journal of Economic Behaviour and</field>
      <field key="Org" subkey="a">nization, 43, 239-262 -- Kirchkamp, O. and R. Nagel (2001): "Repeated Game Strategies in Local and Group Prisoners' Dilemmas</field>
      <field key="Exp" subkey="e">riments: First Results," Homo Ökonomicus, XVIII(2), 319-336 -- Krall, N. and A. Trivelpiece (1986): Principles of Plasma</field>
      <field key="Phy" subkey="s">ics. San Francisco Press -- Tesfatsion, L. and K. Judd (eds.) (forthcoming  2006): Handbook of Computational Economics Vol 2:</field>
      <field key="Age" subkey="n">t-Based Computational Economics. North-Holland;</field>
      <field key="753" subkey="">Abstract: A distributed system model is studied, where individual agents play repeatedly against each other and change their</field>
      <field key="str" subkey="a">tegies based upon previous play. It is shown how to model this environment in terms of continuous population densities of</field>
      <field key="age" subkey="n">t types. A complication arises because the population densities of different strategies depend upon each other not only</field>
      <field key="thr" subkey="o">ugh game payoffs, but also through the strategy distributions themselves. In spite of this, it is shown that when an agent</field>
      <field key="imi" subkey="t">ates the strategy of his previous opponent at a sufficiently high rate, the system of equations which governs the dynamical</field>
      <field key="evo" subkey="l">ution of agent populations can be reduced to one equation for the total population. In a sense, the dynamics 'collapse' to</field>
      <field key="the" subkey="">dynamics of the entire system taken as a whole, which describes the behavior of all types of agents. We explore the</field>
      <field key="imp" subkey="l">ications of this model, and present both analytical and simulation results.;</field>
    </SEQUENTIAL>
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