We propose a novel approach to the modelling of second-price Maximum-Value auctions that assumes no belief about others' behavior and no expected profit maximization. This individual decision-making model, naïve Impulse Balance Equilibrium or nIBE, deals with bidders' anticipated regrets from...

We investigate the role of information feedback in rent-seeking games with two different contest structures. In the stochastic contest a contestant wins the entire rent with probability equal to her share of rent-seeking expenditures; in the deterministic contest she receives a share of the rent...

Overbidding in second-price auctions (SPAs) has been shown to be persistent and associated with cognitive ability. We study experimentally to what extent cross-game learning can reduce overbidding in SPAs, taking into account cognitive skills. Employing an order-balanced design, we use...

We study contests as an example of winner-take-all competition with linearly ordered large strategy space. We study a model in which each player optimizes the probability of winning above some subjective threshold. The environment we consider is that of limited information where agents play the...

Colonel Blotto games with discrete strategy spaces effectively illustrate the intricate nature of multidimensional strategic reasoning. This paper studies the equilibrium set of such games where, in line with prior experimental work, the tie-breaking rule is allowed to be flexible. We begin by...

In this paper, we introduce two new learning models: impulse-matching learning and action-sampling learning. These two models together with the models of self-tuning EWA and reinforcement learning are applied to 12 different 2 x 2 games and their results are compared with the results from...