- author = "Muhammad Iqbal and Will N. Browne and Mengjie Zhang",
- title = "Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems",
- journal = "IEEE Transactions on Evolutionary Computation",
- year = "2014",
- volume = "18",
- number = "4",
- pages = "465--480",
- month = aug,
- keywords = "genetic algorithms, genetic programming, XCS, Learning Classifier Systems, Layered Learning, Scalability, Building Blocks, Code Fragments",
- ISSN = "1089-778X",
-
URL = "
http://homepages.ecs.vuw.ac.nz/~mengjie/papers/",
-
URL = "http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06595603",
-
DOI = "
doi:10.1109/TEVC.2013.2281537",
- size = "16 pages",
- abstract = "Evolutionary computation techniques have had limited capabilities in solving large-scale problems due to the large search space demanding large memory and much longer training times. In the work presented here, a genetic programming like rich encoding scheme has been constructed to identify building blocks of knowledge in a learning classifier system. The fitter building blocks from the learning system trained against smaller problems have been used in a higher complexity problem in the domain in order to achieve scalable learning. The proposed system has been examined and evaluated on four different Boolean problem domains, i.e. multiplexer, majority-on, carry, and even-parity problems. The major contribution of this work is to successfully extract useful building blocks from smaller problems and reuse them to learn more complex, large-scale problems in the domain, e.g. 135-bits multiplexer problem, where the number of possible instances is 2**135 = 4.0 10**40, is solved by reusing the extracted knowledge from the learnt lower level solutions in the domain. Autonomous scaling is, for the first time, shown to be possible in learning classifier systems. It improves effectiveness and reduces the number of training instances required in large problems, but requires more time due to its sequential build-up of knowledge.",
-
notes = "Entered for 2013 HUMIES GECCO 2013
",
