WMC3 - CDA
Recap Problem Statement: We're trying to use GALE to make safety-critical decisions in short time. We're using the CDA model from WMC3, built by Georgia Tech scholars, to learn what organizational structures within the cockpit (in terms of how the pilots should handle their taskload) best optimize objectives such as minimizing time of delay/interruptions in getting these tasks completed. This is a cognitive science domain.
Buggy dataset: http://i.imgur.com/GCZFxie.png. Takes about 12-15 minutes to run 100 times.
Comparing to results (example: http://i.imgur.com/znv2xzv.png) from http://cci.drexel.edu/NextGenAA/pdf/jcedm-2013-Pritchett-measuring%20fa.pdf. This is our main reference paper for sanity checks on the model.
Few obvious correlations. Sanity check.
Task: Figure out the bugs. Then we can take off.
What I did:
Took away all non-determinism (random injections).
Only randomness that exists is with regeneration of individuals - but this isn't really non-deterministic (probability bin distributions).
Results: No change.
Self-reflection: we're mutating some distance, usually going too far. Then we try to come back towards it, and we go too far. Repeat, bouncing back and forth across where we want to go.
Problem: How far do we really want to bounce to get to exactly where we want to go?
Solution: Our projection axis is typically 1.0 units long. In the optimal ideal world, east = 1.0, and west = 0.0 (or vice versa). Thus absolute difference is 1.0 - 0.0 = 1.0. Taking 1 minus this, this tells us how far we need to bounce. "1 - (east - west)".
Observations: In early generations, this bounce distance is on the order of 0.30. In later generations, it's very close to 0.0. In addition, once we get close to 0.0, we STAY there.
Hypotheses: In problems that are hard to optimize, we don't get close to 0.0. Bounce distance tells us on its own how good we're doing.
Some standard Models (Osyczka2, Vienett2, Schaffer): http://i.imgur.com/MUUC2pD.png
POM3 Models: http://i.imgur.com/aSK1gWj.png
GALE POM3B Decision Chart: http://i.imgur.com/zoL8ZiW.png
Observations: Less variance in the dots. Clearer image than before (active v6 link: http://unbox.org/things/var/joe/active/active-v6.pdf)