20 Apr 2018

During last week’s blog post, we had a look at artificial neural networks. These were trained using data where a developer would know the input and correct output. Unlike them the algorithms we are looking today require no supervised learning.


First, we will be taking a look at Self-Organised Maps (SOM). It use...

12 Apr 2018

Where other techniques we discussed were inspired by biologic systems none goes so far as Artificial Neural Networks (ANN). They are directly inspired by how nervous systems, specifically the brain works. They work by finding patterns between various inputs and outputs and adjusting itself to better solve them.

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17 Mar 2018

Case based reasoning (CBR) is a a new method which might looks quite similar to previous rule based examples we have seen previously but has a few key differences.

CBR takes past experiences and categorises them as cases and uses them to solve future problems. The scope of these cases varies from implementation...

16 Mar 2018

Genetic algorithms have long been a favourite subject of mine as there’s something about computing that is inspired by biology that is quite fascinating, almost mystical. After researching the subject and understanding the procedures behind what makes the algorithm work I can see how the implementation is quite...

7 Mar 2018

This week I will be discussing reinforcement learning and Predictive Learning. This marks the departure of discussing non-learning learning algorithm and delving into the world of machine learning. There are three types of machine learning, Supervised, Unsupervised and Reinforcement. We will be looking at two o...

23 Feb 2018

On to fuzzy logic, which is by far the AI technique with the cutest name. It was first formally developed by Dr. Lotfi Zadeh in 1965 and has since then been used in a variety of implementations and projects.

The simple explanation is that while non-fuzzy (called crisp or bivalued logic) values are Binary/Boolean...

14 Feb 2018

Moving on from Finite State Machines from last week, I’ll now be having a look at Rule Based (also known as Expert) systems. They are quite unlike FSM’s in many ways, most strikingly in their ease of implementation. This means that despite their potential to emulate much more complex behaviours than their count...