2 ms·
Achieved a local optimum, not global optimum. One technique to avoid getting stuck in such local optimums is to have some children which have extreme mutations
by em3rgent0rdr 9y ago
Achieved a local optimum, not global optimum. One technique to avoid getting stuck in such local optimums is to have some children which have extreme mutations.
- rcthompson 9y agoYou're making it sound like a simple parameter optimization issue, but it's hard to imagine a mutation that breaks out of the "fall forward as far as possible" paradigm without discarding the parent phenotype entirely, which would defeat the purpose of using an evolutionary algorithm in the first place. Anyway, the point was that a complex optimization problem resulted in an unexpected "suicidal" phenotype, i.e. falling over instead of walking.