Category: Conceptual spaces

Convex regions in a conceptual space are problematic

Recently, another one of my papers [1] (look at the preprint here) has been accepted at the German Conference on Artificial Intelligence. It is a quite technical paper with a lot of formulas, but I’ll try to illustrate the overall high-level idea in this and one or two future blog posts.

Today I would like to talk about the starting point of the research presented in this paper: The observation that convex regions in a conceptual space are highly problematic if we want to represent correlations between domains.

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Where do the dimensions of a conceptual space come from?

This week, the first paper of my PhD research [1] has been accepted for publication (you can take a look at the preprint here). I would like to seize the opportunity and explain here on a high level what this paper is about.

I’ve explained in a previous post what a conceptual space looks like. The aforementioned paper discusses the question posed in the title of this post: “Where do the dimensions of a conceptual space come from?”

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My PhD project in a nutshell

After having covered different topics in my little “What is …?” series, it is now time to put the parts together and explain what my PhD research is all about.

The preliminary title of my dissertation is “Concept Formation in Conceptual Spaces”. As you have probably already guessed, it involves both the area of concept formation and the framework of conceptual spaces.

The basic idea is the following one:

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What are “conceptual spaces”?

After having sketched what hides behind the term “Artificial General Intelligence” in my last post, today I would like to give a short introduction to conceptual spaces.

The term “conceptual spaces” describes a framework proposed by Peter Gärdenfors [1] that aims at a geometric representation of concepts. It is the starting point of my PhD research on concept formation.

But first things first: what is a concept?

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