One fault is that we don't even teach the proper tools in our algorithms courses! There are relatively few algorithms texts that even support the teaching of backtracking as an algorithmic paradigm. Moreover, the sort of very nice work with provable small exponential upper bounds that some theory researchers (e.g., David Eppstein, Richard Beigel, Martin Furer) have done in backtracking algorithms for combinatorial problems is only a very small part of the landscape for algorithmic solutions to hard problems.
Too often, we in theory leave the important hard problems to those in AI and formal methods. One of the standard paradigms in practical verification is to attack problems that in their full generality are PSPACE-hard (or worse), find a useful NP subclass, apply a reduction from these problems to SAT, and use SAT solvers that involve worst-case exponential backtracking (or to a much lesser extent local search) algorithms that are fast in many cases. The key techniques used in these solvers are powerful heuristics that are usually studied in AI but rarely in algorithms research.
The potential for practical impact of improved versions of these algorithms (even with only polynomial speed-up) could be huge. Traditional algorithmic research has occasionally had something useful to say about these topics (such as Moser's recent beautiful analysis of variants of the random walk algorithm on the special classes of CNF formulas satisfying the Lovasz Local Lemma conditions) but it is somehow not viewed as part of the mainstream.
Applications in EDA are only part of the utility of some of the exponential algorithms used in formal methods. There has been a large and surprisingly successful body of work on software model checking that uses quite clever theoretical ideas. One of my favorite examples is the following: Though techniques for checking properties of communicating finite state machines (one of those nasty PSPACE-complete problems) had been in use for EDA since the early 1990's, model checking software presented an additional problem because of the need to handle the call stack. Suppose that one needs to check a safety property (i.e., an invariant). The key observation (which goes back to the early 1960's) is that the language consisting of the possible stack contents of a PDA is always a regular language for which an NFA can be easily constructed from the PDA! One can then apply a small extension the previous algorithm to check safety properties (which must hold for all possible stack contents).
Ruminations on computational geometry, algorithms, theoretical computer science and life
Thursday, July 09, 2009
NSF EDA Workshop: A comment
Paul Beame had a brilliant comment on my post about the EDA Workshop, and I liked it so much I'm reproducing it in full here:
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The algorithms book by Dasgupta-Papadimitriou-Vazirani has a nice chapter on coping with NP-Completeness which discusses both backtrack search as well as local search, approximation, and
ReplyDeletesimulated annealing. I devoted the last lecture in my algorithms class to teaching some of these methods. I like the approach of the book in that it keeps the topics in one place. Kleinberg-Tardos has a nice and detailed chapter on local search but not any discussion on backtrack search.