Lab Notes 1/28/15

January 28, 2015













Gecco Papers -3

Thom, Bill, Nic



Asymmetry on parents

Collaboration with David Clark on math-finite terms and finite algebra, Clark has algorithms that are not evolutionary

Pucks; bonding, will then be able to do push based



Crossover revised paper; 2 problems, crossover bias and tournaments


Lee and Nic-

Measurement of success in systems, best approximation, best fitness

Both metrics are potentially useful, and when you don’t know…


Thom and Nic-

Generalization or how well matches the training set-over fitting?

No validation, but spot-check via graphs; stable, solid approximations over test area

Adding crossover bias-fitness becomes larger



Generalization and how to promote it in GP runs


Lee, Thom and Bill-

Papers from journal; collectively read and discuss

Trade of fitness and validation of fitness

How different system generalize-but not making better at generalization



Promoting generalization in symbolic regression

Smaller programs generally generalize better with better fitness

Random mate selection, survival step-fitness and fitness generality


Lee, Thom and Bill-

2 fitness cases,

Survival-how well fitness to 1, and how well fitness’s compare

2 sets similar-performance on one dependent on other

Size connects to post run simplification

Simplify with hill climber after

Each step turns some genes off (remove sub-expression)



Trees; mutations with replacement of sub tree with parent tree

Preserve syntax


Lee, Bill and Thom-

Post run simplification

Instead of pure hill climbing

Turn off two genes and turn one gene back on

Higher probability of turning things off then on

Frode tried to do systematic testing; same simplification but as genetic operator and how it works with size and generalization; all a wash, simplifying during a run has all sorts of repercussions

Post run simplification for generalization


Bill, Nic and Lee-

Epigenetic paper; danger of varying multiple things and their repercussions and relations within the system

What is the epigenetics contributing? Is it just turning off your other additions?

Tough sell without solving some unsolvable problems

Clarity about base system and what is being changed

Explanation of the nuances of ideas

Rational for starting point

2 stack based systems; epigenetics is easier to do in stack-based systems

What happens when stuff gets turned off?



Push for hill climbing; doesn’t take secondary

Keeps child if better at every test case, even with out lexicase



More LatB data

Calc concentration eq; relates to what the cell looks like

Models with Sarah



Documentation; example programs, how to put in your own data

Java version of push

Unwitting GP, Parasitic computing

Zeke’s tree based GP

Quill, Gorilla repl

Outsiders get started with out intensive tutorial

Cleaner; FourPush?




Trying inductive synthesis with Sketch (having trouble with strings)

Running Tom’s Benchmarks



Thinking about using simplification before parent selection.

Unclear whether this would help.



GECCO Papers



-In tree based GP, the root node is more important.
-Biological Reproduction is generally asymmetric


*GPTP wants “something” by 2/7.

*Gecco Workshop deadlines: 4/3

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