Category knowledge can be explicit, yet not conform to a perfect rule. For example, a child may acquire the rule "If it has wings, then it is a bird," but then must account for exceptions to this rule, such as bats. The current study explored the neurobiological basis of rule-plus-exception learning by using quantitative predictions from a category learning model, SUSTAIN, to analyze behavioral...

In standard models of iterative thinking, there is a fixed rule hierarchy and every player chooses a fixed rule level. Nonequilibrium behavior emerges when some players do not perform enough thinking steps. Existing approaches however are inherently static. In this paper, we generalize models of iterative thinking to incorporate adaptive and sophisticated learning. Our model has three key featu...

Although categorization is fundamental to speech processing, little is known about the learning systems that mediate auditory categorization and even less is known about changes across the life span. Vision research supports dual-learning systems that are grounded in neuroscience and are partially dissociable. The reflective, rule-based system is prefrontally mediated and uses working memory an...

The weight perturbation learning was proposed as a learning rule which adds perturbation to the variable parameters of learning machines. Generalization performance of the weight perturbation learning was analyzed by statistical mechanical methods. The weight perturbation learning has the same asymptotic generalization property as the Perceptron learning. In this paper we consider difference be...

one of the main concerns of iranian students who learnenglish is the fact that they cannot learn the different english rules ofnegative and interrogative tenses and hence suffer from numerous grammar rules.the present study is based on the researchers' experiences, who have beeneducated in linguistics, in teaching english to persian students. they applieda new teaching method (the rule tea...

Rule learning posits that decision makers, rather than choosing over actions, choose over behavioral rules with different levels of sophistication. Rules are reinforced over time based on their historically observed payoffs in a given game. Past works on rule learning have shown that when playing a single game over a number of rounds, players can learn to form sophisticated beliefs about others...

The paper describes an inductive learning environment called DELVAUX for classiication tasks that learns PROSPECTOR-style, Bayesian classiication rules from sets of examples. A genetic algorithm approach is used for learning Bayesian rule-sets, in which a population consists of sets of rule-sets that generate oospring through the exchange of rules, permitting tter rule-sets to produce oospring ...

Understanding the development of non-linear processes such as economic or population growth is an important prerequisite for informed decisions in those areas. In function-learning paradigm, people's understanding function rule that underlies to-be predicted process typically measured by means extrapolation accuracy. Here we argue, however, even though accurate necessitates rule-learning, rever...

Although the role of the striatum in language processing is still largely unclear, a number of recent proposals have outlined its specific contribution. Different studies report evidence converging to a picture where the striatum may be involved in those aspects of rule-application requiring non-automatized behaviour. This is the main characteristic of the earliest phases of language acquisitio...