The integration of different learning and adaptation techniques in one architecture, to overcome individual limitations and achieve synergetic effects through hybridization or fusion of these techniques, has in recent years contributed to a large number of new intelligent system designs. Most of...

We propose a new approach to the pricing and hedging of contingent claims under transaction costs in a general incomplete market in discrete time. Under the assumptions of a bounded mean-variance tradeoff, substantial risk and a nondegeneracy condition on the conditional variances of asset...

In this paper individual overconfidence within the context of an experimental asset market is investigated. Overall, 72 participants traded one risky asset on six markets of 12 participants each. The results indicate that individuals were not generally overconfident. Moreover, overconfidence was...

In this note we study a very simple trial & error learning process in the context of a Cournot oligopoly. Without any knowledge of the payoff functions players increase, respectively decrease, their quantity by one unit as long as this leads to higher profits. We show that despite the absence of...

Updating behavior in cascade experiments is usually investigated on the basis of urn prediction. But urn predictions alone can only provide a very rough information on individual updating behavior. Therefore, we implement a BDM mechanism. Subjects have to submit maximum prices that they are...

To be represented by more than one contestant in a contest has advantages and disadvantages. This paper determines the conditions under which it is favorable to send several agents into the contest. -- contests ; Divisionalization ; delegation

Robust learning experiments confront participants with structurally different decision environments which they encounter, furthermore, repeatedly. Since the decision format does not depend on the rules (of game), forward looking deliberation (the shadow of the future) can be detected by...