By Norman Ehrentreich
From the reviews:
"The booklet below evaluation is a crucial and cautious learn of a few of the problems serious about the workings of the SFI inventory industry. … in my view, Ehrentreich’s e-book is a superb connection with either the training, and empirical literature in finance." (Krzysztof Piasecki, Zentralblatt MATH, Vol. 1141, 2008)
"Norman Ehrentreich used to be one of many bold few to tackle the version, and he has summarized his paintings and findings during this first-class booklet. … it really is worthy primer for a person attracted to getting begun within the quarter of agent-based finance. … it really is crucial analyzing for someone drawn to the dynamics of the SFI industry particularly, yet I additionally suggest it for others as an invaluable source on agent-based monetary marketplace layout as well." (Blake LeBaron, magazine of man-made Societies and Social Simulation, Vol. 12 (2), March, 2009)
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Extra resources for Agent-Based Modeling: The Santa Fe Institute Artificial Stock Market Model Revisited
693]. ” It always requires the use of all our cognitive and computational capabilities—sometimes even beyond that—to perform simple tasks for which simple heuristics would suﬃce. In this respect, procedural or situational rationality, to be deﬁned below, are more economical concepts of rationality. A survey about violations of the basic postulates of economic rationality can be found in . Herbert A. Simon revived the Scottish word ”satisﬁcing” (=satisfying) to denote problem solving and decision making that sets an aspiration level, searches until an alternative is found that is satisfactory by the aspiration level criterion, and elects that alternative [394, Part IV ].
If modeled as individual learning, crossover might be seen as individuals experimenting by combining some of their successful strategies. Mutation Mutation refers to the creation of a new solution from only one parent through spontaneous allele changes. It is an important element of any evolutionary algorithm to prevent premature convergence. Unlike crossover, mutation is able to introduce non-existing alleles at previously homogeneous bit positions. If, for instance, the most signiﬁcant bit is set in none of the trading rules, yet the optimal solution would require it to be set, a GA without mutation could never reach the optimum.
If better information is available, these so-called prior probabilities might diﬀer from each other. , h∈H p(h, t) = 1 must hold for all periods t. As agents learn about new evidence in the next period, they update their initial subjective probabilities associated with each hypothesis according to p(h, t + 1) = P (e(t)|h) · p(h, t) . 1) Through this equation, an observed event increases the probability of that hypothesis for which the occurrence of this event is most likely. 2 Blume and Easley, however, consider the term “rational learning” as a poorly chosen euphemism.
Agent-Based Modeling: The Santa Fe Institute Artificial Stock Market Model Revisited by Norman Ehrentreich