This paper considers the use of neural networks to model bounded rational behaviour. The underlying theory and use of neural networks is now a component of various forms of scientific enquiry, be it modelling artificial intelligence, developing better pattern recognition or solving complex...

This paper explores a model of bounded rationality in evolutionary game play in which agent choice is based on a social psychological process of categorization and social inference. The computer simulation of the model demonstrates that agents' increasing ability to categorize opponents in the...

This paper considers the ‘negotiation game’ (Busch and Wen [4]) which combines the features of two-person alternating offers and repeated games. Despite the forces of bargaining, the negotiation game in general admits a large number of equilibria, some of which involve delay in agreement and...

We explore the consequences of the assumptions used in modern cryptographywhen applied to repeated games with public communication. Technically speaking, we model agents by polynomial Turing machinesand assume the existence of a trapdoor function. Under these conditions, we prove a Folk Theorem...

This paper uses the complexity of non-competitive behaviour to provide a new justification for competitive equilibrium in the context of extensive-form market games with a finite number of agents. This paper demonstrates that if rational agents have (at least at the margin) an aversion for...