Recently I made available some GP code I had in Common Lisp (see previous post). Today I also put on my github account the library I did for Ant Colony Optimzation (cl-aco) and a few others like parsers for MKP and QAP, but also a very basic CFFI bindings for libLBFGS. Like before, these are mostly not to get lost since I’m not using/developing them anymore. But if someone finds this useful in any way, that’s great!
Last week I was at EuroGP where I presented my latest paper “Automatic Design of Ant Algorithms with Grammatical Evolution” (pdf, slides) and it won the Best Paper Award! I am very happy with this distinction since EuroGP is the leading conference on Genetic Programming attended by the best researchers in the field.
In this paper, a Grammatical Evolution approach is used for the automatic design of Ant Colony Optimization algorithms. The used grammar has the ability to guide the learning of novel architectures, by rearranging components regularly found on manually designed variants (for example, the Elitist Ant-System, the Ant Colony System or the Max-Min Ant System). This approach was tested with the TSP and the results show that the evolved algorithmic strategies are effective, exhibit a good generalization capability and are competitive with human designed variants. This is still a starting point and there is a large amount of work to be done but the indications given by these results are encouraging!
This year the conference took place in Málaga, Spain, as part of Evo* as usual. The event was great with an excellent organization lead by Carlos Cotta. It was a fantastic Evo*! Next year it will be held in Wien!
Just received an email with good news! The paper that I got accepted at EuroGP was nominated for Best Paper! The work that I started last year is starting to get some good feedback which is great :-) This paper describes the approach I have developed (in collaboration with Francisco B. Pereira) to evolve pheromone update methods for Ant Systems. The paper only deals with the TSP and the obtained results are promising since it outperforms MMAS. It is the first step to what I am working on, a Self-Ant System. The idea is to let the Ant algorithm find the best components that can help in solving the problem at hand. There is still a lot of work to be done but this is just the start.
For the next days I will be attending PPSN 2010, in Krakow, Poland. I was here for the venue two years ago and it was a conference that I enjoyed very much. Mostly because of the model which is different from the standard ones (poster only format, absence of parallel sessions and a summary presentation of the papers by a senior session chair).
I will be talking about my lastest work which ties together two techniques that I’ve always wanted to do some serious work with them: Ant Systems and Genetic Programming. In this first paper, I am using GP to evolve an Ant System component. A key issue in AS research is how to design the communication mechanism between ants that allows them to effectively solve a problem. We propose in this work to evolve the current pheromone trail update methods. We tested with the TSP and initial results show that the evolved strategies perform well and exhibit a good generalization capability when applied to larger instances.
Doing this work was also very fun and it was all made in Lisp. I just need to improve the code a bit and package it nicely before making it free available.
Anyway, I wish PPSN 2010 will be an interesting conference!