12,598 research outputs found
Setting Parameters by Example
We introduce a class of "inverse parametric optimization" problems, in which
one is given both a parametric optimization problem and a desired optimal
solution; the task is to determine parameter values that lead to the given
solution. We describe algorithms for solving such problems for minimum spanning
trees, shortest paths, and other "optimal subgraph" problems, and discuss
applications in multicast routing, vehicle path planning, resource allocation,
and board game programming.Comment: 13 pages, 3 figures. To be presented at 40th IEEE Symp. Foundations
of Computer Science (FOCS '99
Developing reproducible and comprehensible computational models
Quantitative predictions for complex scientific theories are often obtained by running simulations on computational models. In order for a theory to meet with wide-spread acceptance, it is important that the model be reproducible and comprehensible by independent researchers. However, the complexity of computational models can make the task of replication all but impossible. Previous authors have suggested that computer models should be developed using high-level specification languages or large amounts of documentation. We argue that neither suggestion is sufficient, as each deals with the prescriptive definition of the model, and does not aid in generalising the use of the model to
new contexts. Instead, we argue that a computational model should be released as three components: (a) a well-documented implementation; (b) a set of tests illustrating each of the key processes within the model; and (c) a set of canonical results, for reproducing the model’s predictions in important experiments. The included tests and experiments would provide the concrete exemplars required for easier comprehension of the model, as well as a confirmation that independent implementations and
later versions reproduce the theory’s canonical results
Comparing Typical Opening Move Choices Made by Humans and Chess Engines
The opening book is an important component of a chess engine, and thus
computer chess programmers have been developing automated methods to improve
the quality of their books. For chess, which has a very rich opening theory,
large databases of high-quality games can be used as the basis of an opening
book, from which statistics relating to move choices from given positions can
be collected. In order to find out whether the opening books used by modern
chess engines in machine versus machine competitions are ``comparable'' to
those used by chess players in human versus human competitions, we carried out
analysis on 26 test positions using statistics from two opening books one
compiled from humans' games and the other from machines' games. Our analysis
using several nonparametric measures, shows that, overall, there is a strong
association between humans' and machines' choices of opening moves when using a
book to guide their choices.Comment: 12 pages, 1 figure, 6 table
Spartan Daily, October 17, 1972
Volume 60, Issue 18https://scholarworks.sjsu.edu/spartandaily/5653/thumbnail.jp
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