About half a year ago, I mentioned “Logic Tensor Networks” in my short summary of the Dagstuhl seminar on neural-symbolic computation. I think that this is a highly interesting approach, and as I intend to work with it in the future, I will shortly introduce this framework today.
In one of my previous posts, I’ve shown a little overview diagram of my PhD research. One component of this diagram was called “language games” and so far I have not explained what that means. Well, today I’m going to give a short introduction into this topic.
Language games  focus on the question of “how can language come into existence?”, i.e., “What are possible mechanisms that allow different individuals to come up with a shared vocabulary that they can use to communicate about things in the world?”. I admit that this sounds a bit abstract, so let me illustrate the problem with an example:
In my PhD project, I do research in the area of “concept formation”. Before starting to talk about my PhD research in more detail, I would like to use this post to give a quick introduction into the area of concept formation.
Looking at my posts so far, it seems that a little “What is … ?” series is emerging (“What is AGI?”, “What are conceptual spaces?”). Today I’d like to add another post to this series – this time about the term “machine learning” and about three different types of machine learning algorithms one can distinguish.
As already discussed earlier, “good old fashioned AI” is based on manually writing rules and having some sort of inference system that applies these rules in a given situation. Machine learning is more about discovering rules from a (usually quite large) number of examples.
One can distinguish three types of machine learning: supervised, unsupervised and semi-supervised.
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  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?