Interactions among embedded extensive networks under uncertainty

An extensive game that uses imperfect, potentially asymmetric information and allows the intrusion of nature is presented. Both players are represented by neural network models. These models follow the approaches to decision-making delineated by H. Dreyfus and S. Dreyfus (1986) and the higher-order brain function proposed by Pribram. These views emphasize the fact that brains are inherently synthetic systems whose strengths are derived from parallelism, fault tolerance, and the ability to reconstruct beliefs on the basis of new data. The authors present threefold models of choice which involve automaticity, complex rule construction and rule following, and cortex sensitivity. Misconceptions and resulting distorted outcomes occur