Dynamics of sequential decision making.
We suggest a new paradigm for intelligent decision-making suitable for dynamical sequential activity of animals or artificial autonomous devices that depends on the characteristics of the internal and external world. To do it we introduce a new class of dynamical models that are described by ordinary differential equations with a finite number of possibilities at the decision points, and also include rules solving this uncertainty. Our approach is based on the competition between possible cognitive states using their stable transient dynamics. The model controls the order of choosing successive steps of a sequential activity according to the environment and decision-making criteria. Two strategies (high-risk and risk-aversion conditions) that move the system out of an erratic environment are analyzed.
Rabinovich
Mikhail I
MI
Institute for Nonlinear Science, University of California, San Diego, 9500 Gilman Drive 0402, La Jolla, California 92093, USA. mrabinovich@ucsd.edu
Huerta
Ramón
R
Afraimovich
Valentin
V
D000818:Animals; D001185:Artificial Intelligence; D001522:Behavior, Animal / Q000502:physiology; D003071:Cognition / Q000502:physiology; D003198:Computer Simulation; D003657:Decision Making; D008962:Models, Theoretical