Integrating Logic and Machine Learning

"We may be utilizing machine learning 'too little, too late'.  (IE, we're using too little ML and using ML not early enough).  Thus we may be already going down a slightly wrong path...  we should correct this by taking ML seriously and try to find the best way to incorporate ML in our architecture..." --YKY

interfacing with dANN has been my goal while designing Genifer's Java layer.  when it's finished, it will allow us to combine dANN's components with Genifer concepts.

dANN provides several "machine learning" (and related) components:

• dynamic bayesian networks
• many types of neural networks
• dimensional embedding aka graph drawing
• graph metrics
• etc...

Genifer's logic can remain in LISP -- Java may not be allowed to interfere - but the concepts will be reference-able

LISP will be able to bind formulas to Java method calls.  for example, using graph drawing:

List<Atom> getNeighbors(similarityGraph, center, radius)

so now that we know this, the question becomes: how do we create integrative designs that utilize Genifer and dANN as (internal) components?

well we could create many types of integrative designs.  though we may have a chance to evolve them: we can declaratively instantiate new instances of the system inside itself.

http://picocontainer.org/introduction.html


"Constructor Injection is a Dependency Injection variant where a component gets all its dependencies via its constructor."


"The most important benefits of Constructor Injection are:

• It makes a strong dependency contract
• It makes testing easy, since dependencies can be passed in as Mock Objects
• It is very succinct in terms of lines of code
• Classes that rely on Constructor Injection are generally Good Citizens
• A dependency may be made immutable by making the dependency reference final"

Systems like Picocontainer, and Spring Framework, are used to declaratively specify "wirings" of component dependencies.  This amounts to a hierarchical property tree listing the interfaces, implementation classes, and constant parameters in order to fill a "container" aka "context".

more later on this...