Entropic Decision Making

Document pages: 84 pages

Abstract: Using results from neurobiology on perceptual decision making and value-baseddecision making, the problem of decision making between lotteries isreformulated in an abstract space where uncertain prospects are mapped tocorresponding active neuronal representations. This mapping allows us tomaximize non-extensive entropy in the new space with some constraints insteadof a utility function. To achieve good agreements with behavioral data, theconstraints must include at least constraints on the weighted average of thestimulus and on its variance. Both constraints are supported by theadaptability of neuronal responses to an external stimulus. By analogy withthermodynamic and information engines, we discuss the dynamics of choicebetween two lotteries as they are being processed simultaneously in the brainby rate equations that describe the transfer of attention between lotteries andwithin the various prospects of each lottery. This model is able to give newinsights on risk aversion and on behavioral anomalies not accounted for byProspect Theory.