I'm reading through a new book, Compositional Evolution by Richard Watson, and it is really interesting. Watson's thesis is that certain evolutionary methods of variation (sexual recombination, lateral gene transfer, symbiotic encapsulation, etc.) are fundamentally distinct in an algorithmic sense from the traditional gradualist framework (in which beneficial mutations are accumulated in a linear fashion). Gradualism operates as a hill-climbing search strategy, and is therefore prone to get stuck in local optima. Compositional mechanisms, on the other hand, are apparently able to escape them (in systems with a semi-modular relationship among their variables) by combining pre-adapted genetic data from two distinct lineages.

Watson is a computer scientist, and examines evolution from an algorithmic perspective. The admission and proof of the inability of gradualism to evolve systems with strong dependencies among its variables is refreshingly frank. He presents a substitute mechanism, of course, so the book is not supportive of ID. Still, it helps formalize and highlight the issues involved, in a way that makes them easier to talk about. Computational Evolution is definitely worth a read if you're interested in looking at evolution from an algorithmic perspective – especially if you'd like to critically evaluate the power of evolutionary search strategies.