Swamidass:
I will start with an easy point: your question about neutral drift. I think that will be valid for coevolution also.
First of all, I am well aware of nutralism and of drift as important actors in the game. Indeed, you can see that my whole reasoning to measure FI is based on the effects of neutral variation and neutral drift. What else erases non functional similarities given enough evolutionary time?
So, I have no intention at all to deny the role of neutral variation, of neutral drift, and of anything else that is neutral. Or quasi neutral.
My simple point is: all this neutral events, including drift, are irrelevant to ID and to FI.
The reason is really very simple. FI is a measure of the probability to get one state from the target space by a random walk. High FI means an extremely low probability if reaching the target space.
Well, neutral drift does not change anything. The number of states that is tested (the probabilistic resources of the system) remains the same. The ratio of the targte space to the search space remains the same. IOWs, neutral drift has no influence at all on the probabilistic barriers.
Why? Because it is a random event, of course. Each neutral event that is fixed is a random variation. There is no reason to believe that the mutations that are fixed are better than those that are not fixed, in the persepctive of getting to the target. Nothing changes.
Look, again I am trying to answer briefly. But I can deepen the discussion, if you let me know what you think.
Just a hint. To compute FI in a well defined system, we havt to compute, durectly or indirectly, three different things:
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The search space. That is usually easy enough, with some practical approximations.
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The target space. This is usually the difficult part, and it usually requires indirect approximations.
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The probabilistic resources of the system. FI (-log2 the ratio of the target space to the search space) is a measure of the improbability of finding the target space in one random event. But of course the system can try many random events. So, we have to analyze the probabilistic resources of the system, in the defined time window. This can usually be donne by considering the number of reproductions in the population, and the number of mutations. IOWs, the total number of genetic states that will be available in the system in the time window.
I have discussed many aspects of these things in this OP:
I give here also the link to my OP about the limits of NS:
What Are The Limits Of Natural Selection? An Interesting Open Discussion With Gordon Davisson
In those two OPs, and in the following discussions, I have discussed many aspects of the questions that are being raised here. Of course, I will try to make again the important points. But please help me. When what I say seems too brief or not well argumented, consider that I am trying to give the general scenario first. Ask, and I will try to answer.