Present
Lee, Tom, Frode, Kwaku, Karthik, Eddie, Omri (scribe)
Reminders
Lee: send out a CI Lab email about Zeke’s webgp thing
GECCO deadlines: Jan. 15th for abstracts, 29th for papers, and they seem very serious about sticking to these deadlines
Administrative stuff
There will probably be a meeting next Wednesday, regular time, last of the semester
Proposed Clojush changes
All println calls to prn
Option to report percent of parens in a given program or population
Separate out “report-best”, so that it can be independent from “fitness”
Pysh
It works (yay!)
Some of the syntax is different
Next steps are to include tags and/or any kind of genetic programming functionality
Lee recommends aiming to make it usable for next semester’s Genetic Programming students
Clojush documentation
Frode has been working on this, with a lot of good documentation and tutorials that can be seen in the Clojush wiki
Lee is unsure where we should go from here: where to host documentation and tutorials of Clojush and/or of Push in general
Evolving GUIs and “reactive” Push REPL
Frode has been thinking about doing experiments related to both of these
Lee pointed out that these are separable projects, and that one possible off-shoot is to look into some Excel/Clojush integration
Parameter tweaking in evolutionary runs
Bill has been trying to solve a harmonic oscillation problem
He has a number of interesting non-standard genetic operators that he’s been working with, and is having difficulty knowing/finding the right parameters
Lee suggested taking a step back and trying more standard genetic operators, and also just “seeing what works”
Modules
Karthik would like to do some experiments here, possibly related to the calculator problem
Lee described a lot of recent efforts around automatic modularity, and the various issues surrounding modularity in general
Kwaku has been working on identifying modularity at run-time, hoping to find good metrics for modularity in arbitrary programs (which reminds Lee of some old experiments testing the “compressibility” of execution traces in Push programs)
Word count problem
Thom thinks he’s recently come upon some general solutions to the word count problem (yay!)
Training cases and test cases
Tom’s using training AND test cases, where training cases are seen during evolution, and test cases are only used to test the generality of solutions that arise from the evolutionary loop
Lee has a sort of rotating-auto-generation training case thing, but notes that he doesn’t know what’s going on between generations because of the set of cases shifting under his feet
Tom suggests making one large auto-generated list of cases, choosing a random subset for evolutionary selection, and using the whole thing for comparing different generations
Non-elite lexicase
Lexicase seems to have issues with errors measured in floating point, because selection here will be too elite
So Tom has been experimenting with a non-elite lexicase based on relative ranking (“ranked lexicase”): notably, on the bioavailability problem, it was better than normal lexicase, but equal to standard tournament selection
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