The design and analysis of an adaptive strategy for N-person averaged constrained stochastic repeated game are addressed. Each player is modeled by a stochastic variable-structure learning automaton. Some constraints are imposed on some functions of the probabilities governing the selection of the player's actions. After each stage, the payoff to each player as well as the constraints are rando...

A method for calculating genetic drift in terms of changing population fitness variance is presented. The method allows for an easy comparison of different selection schemes and exact analytical results are derived for traditional generational selection, steady-state selection with varying generation gap, a simple model of Eshelman’s CHC algorithm, and (μ + λ) evolution strategies. The effects ...

Loading of data from slow persistent memory (disk storage) to main memory represents a bottleneck for current interactive visual data exploration applications, especially when applied to huge volumnes of data. Semantic caching of queries at the client-side is a recently emerging technology that can significantly improve the performance of such systems, though it may not in all cases fully achie...

The auxiliary problem principle is a powerful tool for solving multi-area economic dispatch problem. One of the main drawbacks of the auxiliary problem principle method is that the convergence performance depends on the selection of penalty parameter. In this paper, we propose a self-adaptive strategy to adjust penalty parameter based on the iterative information, the proposed approach is verif...

We derive a simple accuracy matching strategy for inexact Gauss Newton methods and apply it to the numerical solution of boundary value problems of ordinary diierential equations by collocation. The matching strategy is based on an aane contravariant convergence theorem, i.e., the characteristic constants are invariant under aane transformations of the domain. The inexact Gauss Newton method is...

This paper presents an evaluation study that compares two different problem selection strategies for an Intelligent Tutoring System (ITS). The first strategy uses static problem complexities specified by the teacher to select problems that are appropriate for a student based on his/her current level of ability. The other strategy is more adaptive: individual problem difficulties are calculated ...

In this paper we describe our image annotation system participated in the ImageCLEF 2014 scalable concept image annotation task. The system is fully SVM based. Per concept we learn an ensemble of fast intersection kernel SVMs from three sources of training data, all obtained with manual annotation for free. The focus of our experiments this year is to answer the question of how many tags we sho...

⎯The convergence of genetic algorithm is mainly determined by its core operation crossover operation. When the objective function is a multiple hump function, traditional genetic algorithms are easily trapped into local optimum, which is called premature convergence. In this paper, we propose a new genetic algorithm with improved arithmetic crossover operation based on gradient method. This cro...

This paper presents an experimental study of different variants of tournament selection, and proposes a new DISPAR-tournament (Disjoint Sets Parallel tournament) operator for population reduction to be used in parallel implementations of evolution strategies and other evolutionary algorithms.