This paper surveys locally weighted learning, a form of lazy learning and memory-based
learning, and focuses on locally weighted linear regression. The survey discusses distance …

Many lazy learning algorithms are derivatives of the k-nearest neighbor (k-NN) classifier,
which uses a distance function to generate predictions from stored instances. Several …

The problem of consciousness continues to be a subject of great debate in cognitive
science. Synthesizing decades of research, The Conscious Brain advances a new theory of …

Four experiments investigated the influence of categorization training on perceptual
discrimination. Ss were trained according to 1 of 4 different categorization regimes …

Psychological theories of categorization generally focus on either rule-or exemplar-based
explanations. We present 2 experiments that show evidence of both rule induction and …

According to one productive and influential approach to cognition, categorization, object
recognition, and higher level cognitive processes operate on a set of fixed features, which …

Human categorization is one of the most important and successful targets of cognitive
modeling, with decades of model development and assessment using simple, low …

Previous work has shown that predictive coding can provide a detailed explanation of a very
wide range of low-level perceptual processes. It is also widely believed that predictive …

Several well-developed approaches to inductive learning low exist, but each has specific
limitations that are hard to overcome. Multi-strategy learning attempts to tackle this problem …

In this paper we propose that the conventional dichotomy between exemplar-based and
prototype-based models of concept learning is helpfully viewed as an instance of what is …