Evolutionary algorithms in theory and practice
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..., 2001), which can be simulated with evolutionary algorithms (Klockgether and Schwefel, 1970; Rechenberg, 1973; Schwefel, 1977; Baeck, 1996). For example, pedestrians have a preferred side for walking (Oeding, 1963; Older, 1968; Weidmann, 1993), since an asymmetrical avoidance behavior turns out to be profitable (Bolay, 1998). The related formation of a behavioral convention can be described by means of evolutionary game theory (Helbing, 1990, 1991, 1992a, 1992c, 1993a, 1995a, 1996c). Another requirement is the vectorial additivity of the separate force terms reflecting different environmental influences and psychological factors. This is probably an approximation, but there is some experimental evidence for it. Based on quantitative measurements of animals and human test subjects receiving separately or simultaneously applied stimuli of different natures and strengths, one has shown that behavior in conflict situations can be described by a superposition of forces (Miller, 1944, 1959; Herkner, 1975). This fits well with the concept of Lewin (1951), according to which behavioral changes are guided by social fields or social forces, an idea that has been put into mathematical terms by Helbing (1991, 1992a, 1993b, 1994, 1995a; see also Helbing and Molnár, 1995)....
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...This automatic behavior can be interpreted as the result of a learning process based on trial and error (Helbing et al., 2001c), which can be simulated with evolutionary algorithms (Klockgether and Schwefel, 1970; Rechenberg, 1973; Schwefel, 1977; Baeck, 1996)....
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..., 2001), which can be simulated with evolutionary algorithms (Klockgether and Schwefel, 1970; Rechenberg, 1973; Schwefel, 1977; Baeck, 1996)....
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