First, what I liked about the paper. I like the idea of the local search strategy vs. a global search strategy. I would be interested to see further development of how well use of local information suits the web environment as it is today. I also like the idea of a simulated web environment. A simulated web environment allows an experimenter to keep the environment constant among runs of different algorithms (such as download times, network load and latency and page availability). However, I don’t think that I got a very strong feeling for what was entailed in the simulation environment and how well the environment actually fit the web.

I had a few problems with the general agent representation and also the experimentation. The idea of examining the web based on local information instead of a large global representation is definitely interesting. However, I found the concepts of agents, energy and mutation slightly confusing. I think that the same algorithm could have been presented much more clearly without the concepts of actual agents and more in the framework of a basic randomized algorithm (possibly multithreaded).

Finally, I think that much better experimental results should have been presented. Although BFS and randomized local search are decent baselines to measure against, it is difficult to conceive of any semi-decent algorithm doing worse than these two algorithms. I think a better comparison would be some intelligent crawler that uses information found on pages (similar to those designed and researched for 250A).