Notes on the simulation of evolution

摘要: The simulation of evolution for the purposes parameter optimization has generally demonstrated itself to be a robust and rapid technique. But there may exist more value in simulating than simple optimization. optimizations system behavior obtained through simulated represent potentially powerful autopoetic pathway machine learning self-organization. Indeed, it eventually prove only practical path development ontogenetic intelligence. As complexity systems being evolved increases, proper philosophy analysis design becomes imperative. designer evolutionary algorithms must keep clearly mind what is evolves by consequence. Notes on are offered four sections: 1) basic nature evolution, 2) its simulation, 3) common philosophical errors, 4) that which remains accomplished. Simulated mechanism can reasonably expected continue grow importance benefit. availability massively parallel processors techniques will become increasingly apparent, if no other reason natural match between technique emerging technology. method been repeatedly successfully find points global optimality when methods fail, often astonishingly quickly. Specific rules have apparent easily stated. >