In this paper, we outline a comprehensive approach to composed analogies based on the theory of conceptual spaces. Our algorithmic model understands analogy as search procedure and builds upon idea that analogical similarity depends phenomena called ‘dimensional salience.’ We distinguish between category-based, property-based, event-based, part-whole analogies, propose computationally-oriented ...

In this paper we present two fuzzy models for the description of the process of AR by representing its main steps as fuzzy subsets of a set of linguistic labels characterizing the individuals’ performance in each step. In the first model we used the ShannonWiener diversity index as a measure of the individuals’ abilities in analogical problem solving, while in the second one we measure the indi...

Since spoken language is characterized by a number of properties that defy interpretation and translation by purely grammar-based techniques, recent interest has turned to analogical (also known as case-based or example-based) approaches. In this framework, the most important step consists of robustly matching the recognized input expression with the stored examples. This paper presents a proba...

The paper considers the problem of completing a set of parallel if-then rules that provides a partial description of how a conclusion variable depends on the values of condition variables, where each variable takes its value among a finite ordered set of labels. The proposed approach does not require the use of fuzzy sets for the interpretation of these labels or for defining similarity measure...

One challenge faced by cognitive systems is how to organize information that is learned by reading. Analogical reasoning provides a method for immediately using learned knowledge, and analogical generalization potentially provides a means to integrate knowledge across multiple sources. To use analogy requires organizing information into effective cases. This paper argues that using connectivity...

Recently there has been a surge of interest in using structural priming to examine sentence production. We present an analogical model of sentence production that exhibits structural priming effects. It uses analogical generalization to acquire abstract language patterns from experience. To construct utterances, it uses analogical retrieval to find semantically similar utterances and generaliza...

The EBG system builds an explanation and learns a concept de nition as its generalization provided a domain theory is complete. It does not work when a domain theory is incomplete. Then we introduce a notion of generalizations by an analogy which makes it possible to construct rules necessary for domain theories. Furthermore, we develop EBG by analogical reasoning which copes with the incomplet...

The acquisition of relational concepts plays an integral role and is assumed to be a prerequisite for analogical reasoning. Language and token-trained apes (e.g. Premack, 1976; Thompson, Oden, and Boysen, 1997) are the only nonhuman animals to succeed in solving and completing analogies, thus implicating language as the mechanism enabling the phenomenon. In the present study, I examine the role...

Three theories of analogy have been proposed that are supported by computational models and data from experiments on human analogical abilities. In this article we show how these theories can be unified within a common metatheoretical framework that distinguishes among levels of informational, behavioral, and hardware constraints. This framework clarifies the distinctions among three computatio...

Fluid intelligence is the ability to think flexibly and to understand abstract relations. People with high fluid intelligence (hi-fluIQ) perform better in analogical reasoning tasks than people with average fluid intelligence (ave-fluIQ). Although previous neuroimaging studies reported involvement of parietal and frontal brain regions in geometric analogical reasoning (which is a prototypical t...