ok, np actually, I'm proceeding with my own pace.
Project as such has no deadlines.
Intermediate deadlines can just help to coordinate efforts.
If you start driving some area, planning will do have the meaning.
Let me explain what is happening now:
Q2 is away currently, Q3 is in the middle.
Q2 results are:
Migration to free IDE:
After trying several times to work with Codelight, especially with
debug - I decided to revert to Visual C,
I have downloaded VC 2010 Express Edition, which is free, registered
it and I'm now using it
I created solution Engine+Generic (still the same principles - copy
binaries).
All sources were committed.
Project files - are not, as still not clear what to commit and how to
work with it in version control.
If include all sources from all folders - it will be compiled
successfully.
Repeat folders in file tree in VC project.
Run is available now.
Auto-build and deployment - thrown away as not required
Libraries:
Changed my mind re principal approach - w/o solving practical things
it is impossible to prepare required libraries.
So I'm now trying to create AI engine as is and will add required
libraries when needed.
Not any library, but 2 types of libraries - Artificial Neural Networks
and Belief Networks.
Also I created multi-implementation framework - each type of library
can be represented by several implementations - from any source.
Also I'm confident that to move ahead with visible speed, the project
should re-use existing open source libraries w/o trying to rewrite
them as discussed before.
To reduce mess, current view is that facade interfaces should be
created for any inter-module call.
Test classes were detached from modules and combined within one test
module.
Test classes can reference any intra-module class directly w/o using
module interfaces, using private module include files.
Architecture:
Not sure it is final - but it is more plausible and practical compared
to previous one
Read aiengine\src\_wallpaper.txt
Project structure is almost the same as in architecture picture.
I'm now creating initial flow, starting from some primitive sensors.
I've implemented some starting model brain (not mind!) which has
ongoing focus in form of fixed set of networks, currently processed by
thread pool (all is configurable).
Inter-area connections, intra-area connections are my current interest
- with Hebbian learning.
Area is constructed and then processed (calculated, evolved) not by
brain component, but by dedicated mind component.
Again, the next question is how to convert sensing data into
(internal) features.
So HTM is still actual thing - but only in the context of real tasks.
Let' name it continuous integration.
Please let me know your thoughts and area.