GECCO - days 3, 4 and 5

I'm very sorry I didn't post updates on GECCO as it went. I was quite busy at the conference as well as tired at the end of the day(s). So I'll sum up the three days of the main conference in this one post.

Day 3

It was the first day of the main conference, i.e. the part where the full papers were presented in a 25 minutes long talks (20 + 5 for questions and discussion). It started with a keynote by Ricard Solé from Universitat Pompeu Fabra entitled „Re-designing Nature with Synthetic Biology: from Artificial Ants and Tissues to a New Biosphere“. He talked about designing new organisms to do useful stuff like fixing cracks in concrete or repairing damaged land. To be honest I didn't understand most of it very much but it was interesting.

Here are two interesting talks I have visited. They are not the only ones but these I find the most interesting and having the highest impact on my own research.

Building Predictive Models via Feature Synthesis

A great talk given by Una-May O'Reilly, from MIT, introduced a new approach for building predictive models. It is based on Genetic Programming and LASSO, a linear regression method that penalizes coeffitients size. I still have to read the paper but from what was told during the talk, but this is really a step forward in evolutionary machine learning as it is supposed to be fast and produce good models.

Examining the „Best of Both Worlds“ of GE

This talk I would call „a bad day for GE“. GE, or Grammatical Evolution, is an algorithm for Genetic Programming which happens to be the one I use very extensively (I promise I will write about this! Really! Sometimes...). In his talk, Peter A. Whigham has shown that the GE is not as good algorithm as it is thought of. In fact he has shown that it is only a little bit better than random search. If one wants to use grammar-based GP approach he recommends to use Context-free Grammar Genetic Programming (CFGGP), an approach older than GE.

Day 4

The fourth day, or the second day of the main conference, started with a keynote by Kate Smith-Miles from the Monash University, entitled „Visualising the Diversity of Benchmark Instances and Generating New Test Instances to Elicit Insights into Algorithm Performance“. The title sounds scary but it really is not that. Kate described the problem of current algorithm research procedure:

1. Propose a new algorithm which is (usually) a minor variation on the existing ones.
2. Measure the performance on this, this ... and this benchmark.
3. Report that my new algorithm is overall a little bit better than the state of the art.
4. Publish a paper.

She argued that this approach can only show strengths of the algorithm and not its weaknesses, and she raised a question whether the benchmarks that are commonly being used are really that diverse. She continued on with her talk by demonstrating a new approach for performance measurement of algorithms by computing features of the problems, projecting this space into 2D and there visualising the areas where particular algorithms are the most effective and where lay their weaknesses.

Interactively Evolving Compositional Sound Synthesis Networks

An interesting talk at the Digital Entertainment Technologies and Arts track given by Amy Hoover. The research she presented was about using CPPNs evolved by NEAT to produce sound synthesisers. All this happens through an interactive evolution, i.e. the user manually selects which „solutions“ are good. After all, you can try the very product of the research here. http://bthj.is/breedesizer/

An Efficient Structural Diversity Technique for Genetic Programming

The first of the three best paper nominees in the Genetic Programming track. The talk itself was not that great but the presented research, or the idea behind it, is brilliant. It was about enhancing diversity in GP, but with a very very simple yet powerful mechanism: you record first (few) levels of the trees, called genetic markers, and you record a „density“, or how many individuals have the same genetic marker, and you then use some multi-objective paradigm to optimize both the fitnes and the density.

Genetic Programming with Epigenetic Local Search

Second of the best paper nominees. The talk was about an epigenetic search in GP. In biology, epigenetics is a subfield of genetics which looks at the changes in gene expression other than the changes in the DNA (very simplified). Here it meant the ability of parts of the genotype to be simply switched off. Since this would be very difficult to do with classical tree GP, the Lee Spector's Push language was used. The genotypes simply carry a bit for each element in the genotype which simply means whether this element is to be used or not. The epigenetic local search then plays with these bits.

Memetic Semantic Genetic Programming

The last of the best paper nominees and actually the one that won (though I voted for the first one). The research was focused on GP for boolean algebra (and extended for finite algebras). The „trick“ was to analyze where an individual is wrong and repairing the subtrees that cause it to be wrong, using a static library of trees generated once at the start.

Day 5

The last day of the conference. It started with a „ceremony“ where best paper winners were presented, as well as the winners of competitions and other awards. Then the next GECCO place was presented, which is going to be Denver, Colorado, USA.

After the ceremony there was the last keynote, given by Manuel Martín-Loeches from Complutense University of Madrid entitled „Origins and Evolution of Human Language: Saltation or Gradualism?“. And as the title says, it was about the evolution of the human language. It was very interesting and the message is that Manurel Martín-Loeches stands by the theory that the language was a result of gradual evolution by small mutations, rather than one (or a few) big macro-mutation(s).

The last session of GECCO did not have any talks that were very relevant for my research so I looked mostly for things that were just interesting...

Novelty Search for Soft Robotic Space Exploration

An interesting talk about using Novelty Search for evolving soft robots for space exploration. The research was focused on evolving robots made of soft materials of varying properties for exploration of other bodies, like the Moon or Mars. It used indirect encoding by means of evolving CPPNs that produce the robot instead of evolving the robot directly. The CPPN told whether a voxel is to be filled with the material and if yes then with which material. The presentation was quite funny because the presenter showed us videos of the evolved robots moving, some of which being very funny.

Final summary

This was my first GECCO and also my first conference of such magnitude. In my opinion the conference ran very smoothly, there were no problems. I successfuly presented both my papers, one at the Student Workshop and the second one in the regular poster session. I had a chance to talk with other researchers and students which was quite nice. To sum up, I consider GECCO 2015 to have been great and I hope it was not the last one for me.