This paper deals with the problem of integrating most suitable feature selection methods for a given in order to achieve best order. A new, adaptive and hybrid approach is proposed, which combines utilizes multiple individual more generalized solution. Various state-of-the-art are presented detail examples their applications an exhaustive evaluation conducted measure compare performance propose...

Question: We examine strategy dynamics for evolutionary games with vector-valued strategies. Mathematical methods: We use the fitness-generating function (G-function) to derive ESS maximum principle and strategy dynamics along multi-dimensional adaptive landscapes. We apply the dynamics to two models of co-evolution of competitors and one model of predator–prey co-evolution. Results: When sever...

We investigate the equilibrium selection problem in n-person binary coordination games by means of adaptive play with mistakes (Young 1993). The size and the depth of a particular type of basins of attraction are found to be the main factors in determining the selection outcome. The main result shows that if a strategy has the larger basin of attraction, and if it is deep enough, then the strat...

People often compare sets of numbers informally, in considering prices or sports performance. Children who lack knowledge of formal comparison strategies (e.g., statistics) may use intuitive strategies like estimation that create summary values with approximations of means and variance. There were two goals for this experiment: (1) to classify data comparison strategies and (2) to evaluate whet...

This paper is concerned with the problem of designing a robust adaptive controller for flexible joint robots (FJR). Under the assumption of weak joint elasticity, FJR is firstly modeled and converted into singular perturbation form. The control law consists of a FAT-based adaptive control strategy and a simple correction term. The first term of the controller is used to stability of the slow dy...

The paper aims at designing new strategies to extend the selection step of traditional Differential Evolution for Multi-objective Optimization algorithm to proficiently obtain Pareto-optimal solutions in presence of noise. The first strategy, referred to as adaptive selection of sample size, is employed to balance the trade-off between accurate fitness estimate and computational complexity. The...

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number ...