AI

You’ve only got so many resources and you want to maximise your profit or minimise your costs. How are you going to figure out what to do? Prolog with CLP(fd) of course!

Transitive relations show up a lot in AI code, in this post we look at a couple of ways to code them that depend on what you can assume about your domain and what Prolog you're using.

Reification is a tool in the bag of tricks that can be quite tricky to understand. Rather than waffle on in the abstract, let's take a look at a few examples.

Under the open world assumption a fact can be True, False or Unknown. Prolog operates in a closed world where predicates are either True or False. Let's see if we can open Prolog up a little.

If you've been doing some reading, you may have come across the notion of frames as a data structure, but little available information on what they are and how they work. Implementations of frames are even rarer. In this post we'll examine what they are and consider alternative representations and implementations.

When we start doing knowledge representation in Prolog, we start needing to describe the properties of relations so we can infer more than is in our recorded data. Symmetry, reflexivity and transitivity are the three main relationship properties you'll end up using. In this interactive post we take a look at how they can be encoded.