Compute-intensive methods in artificial intelligence Bart Selman Department...  Home/Search
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Abstract: ra, and was open for over sixty years. The computer proof was found by applying powerful search techniques guided by general search tactics. Several aspects of the computer proof could be called "creative" by mathematicians' standards. Deep Blue's performance and the resolution of Robbin's theorem are good examples of a qualitative change in performance of compute-intensive approaches compared to just a few years ago. In my own work, I have focused on compute-intensive methods in a range of... (Update)
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BibTeX entry: (Update)
@misc{ in-annals,
author = "Compute-Intensive Methods In",
title = "Annals of Mathematics and Artificial Intelligence 28 (2000) 35--38 35 Perspectives",
url = "citeseer.ist.psu.edu/679434.html" }
Citations (may not include all citations):329 Where the really hard problems are - Cheeseman, Kanefsky et al. - 1991
320 Hard and easy distribution of SAT problems - Mitchell, Selman et al. - 1992
103 Local search strategies for satisfiability testing - Selman, Kautz et al. - 1993
97 Knowledge compilation using Horn approximations - Selman, Kautz - 1991
81 Critical behavior in the satisfiability of random Boolean ex.. - Kirkpatrick, Selman - 1994
62 Solution of the Robbins problem - McCune - 1997
60 Knowledge compilation and theory approximation - Selman, Kautz - 1996
47 Learning evaluation functions for global optimization and Bo.. - Boyan, Moore - 1998
40 Pushing the envelope: planning (context) - Kautz, Selman - 1996
35 A survey on knowledge compilation - Cadoli, Donini - 1998
32 phase transitions (context) - Monasson, Zecchina et al. - 1999
30 High-performance job-shop scheduling with a time-delay TD - Zhang, Dietterich - 1996
23 Near-optimal plans (context) - Selman - 1994
12 Stochastic search and phase transitions: AI meets physics (context) - Selman - 1995
12 Challenge problems for artificial intelligence - Selman, Brooks et al. - 1996
11 GSAT: A new method for solving hard satisfiability problems (context) - Selman, Levesque et al. - 1992
10 Control knowledge in planning: benefits and tradeoffs - Huang, Selman et al. - 1999
8 Computational challenges in propositional reasoning and sear.. (context) - Selman, Kautz et al. - 1997
7 Learning declarative control rules for constraint-based plan.. - Huang, Selman et al. - 2000
3 The day that I sensed a new kind of intelligence (context) - Kasparov - 1996
3 Artificial Intelligence Magazine (context) - Weld, in et al. - 1999
2 Computer math proof shows reasoning power (context) - Kolata - 1996
2 An empirical evaluation of knowledge compilation - Kautz, Selman - 1994
1 See ftp://ftp (context) - McDermott, computers et al. - 1997
1 Unifying SAT-based and graph-based planners (context) - Kautz, Selman - 1999
1 Phase transitions in problem solving (context) - Hogg, Huberman et al. - 1996
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