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We examine opportunistic evolution, a variation of master-slave distributed evaluation designed for deployment of evolutionary computation to very large grid computing architectures with limited communications, severe evaluation overhead, and wide variance in evaluation node speed. In opportunistic evolution, slaves receive some N individuals at a time, evaluate them, and then run those individuals through their own mini evolutionary loop until some fixed wall clock time has been exceeded. Our implementation of opportunistic evolution may be used in conjunction with either a generational or, for maximum throughput, an asynchronous steady-state evolutionary model in the master. Opportunistic evolution is strongly exploitative. We perform initial experiments comparing the technique with a traditional master/slave model, and suggest possible classes of problems for which it might be apropos.