Games of Competition in a Stochastic Environment

The paper presents a set of games of competition between two or three players in which reward is jointly determined by a stochastic biased mechanism and players’ choices. More specifically, a resource can be found with unequal probabilities in one of two locations. The first agent is rewarded only if it finds the resource and avoids being found by the next agent in line; the latter is rewarded only if it finds the former. Five benchmarks, based on different psychological and game-theoretic assumptions are derived and their predictions compared to actual behavior of 120, 40, and 48 participants playing repeatedly. Of the five benchmarks—the unique (Nash) equilibrium, reinforcement learning, trust-based efficiency, maximum unpredictability, and regret-based (Impulse Balance) equilibrium—regret for missed opportunities best accounts for the qualitative aspect of participants’ behavior and regret attenuated by randomization best accounts for the quantitative aspect of behavior.     

An optimized model for substitution of expatriate workforce in a Gulf-Council country: the Kuwaiti case

"This article is based on data from a research project carried out during 1992-1994 to achieve a replacement mechanism and a model for the substitution of expatriate labour by Kuwaiti nationals. Since Kuwait can readily enforce its Kuwaitization policy in the public sector, the presented model aims at reducing the share of non-Kuwaitis in that sector over five years. Published data on distribution of the workforce in the public sector by nationality indicate that the non-Kuwaiti share of the total workforce is 38 per cent. The majority of [migrant] workers are unskilled or semi-skilled and engaged in production, commerce and services. Sex ratios are unbalanced and workers exhibit a high rate of literacy...." (SUMMARY IN FRE AND SPA)     

LLL-reduction for integer knapsacks

Given a matrix A∈? ^m×n satisfying certain regularity assumptions, a well-known integer programming problem asks to find an integer point in the associated knapsack polytope or determine that no such point exists. We obtain an LLL-based polynomial time algorithm that solves the problem subject to a constraint on the location of the vector b.     

Lower bounds for expected sample size of sequential procedures for the multinomial selection problems

In this article, lower bounds for expected sample size of sequential selection procedures are constructed for the problem of selecting the most probable event of k-variate multinomial distribution. The study is based on Volodin’s universal lower bounds for expected sample size of statistical inference procedures. The obtained lower bounds are used to estimate the efficiency of some selection procedures in terms of their expected sample sizes.