I have long been interested in machine learning, AI, datamining, etc. One of the recently emerging (but not that ‘new’) areas in this space is Artificial Immune Systems (AIS).  Here is a great article for the beginner on the topic. It has examples in Delphi (pleasantly with unit tests). More importantly - it has nice pictures and explains the basics simply enough.

One of the things that I think is really interesting about this space is that there are lots of hybridizations. It is common to be using neural nets, evolutionary algorithms, AIS and reams of other techniques in one solution. The  No Free Lunch Theorem suggests that there will really never be a ’super algorithm’ that can work to solve all sorts of machine learning (and/ or optimization) problems with equal ability. This further implys that there will continually be the need for new algorithms/ techniques and tools to solve different kinds of problems. Put in the light of hybridized solutions for machine learning - the implication is that there will be lots of components to solve complex datamining/ optimization/ machine learning etc. problems. I am always enthusiastic when I see yet another emergent technique like AIS because this means that the components available to solve harder and harder problems are becoming available. The challenge of course is effectively understanding and combining these elements into effective devices for solving problems.

A few other interesting tangents

Swarm Intelligence
Ant Colony Optimization
Memetic Algorithms

A few great resources can take you far - they do cost a few $ however:

MIT Journal of Evolutionary Computation
IEEE Computer Society
IEEE Computational Intelligence Society

All great stuff

-Chris

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