Using Uncertainty Within Computation
Papers from the 2001 Fall Symposium
Carla Gomes and Toby Walsh, Program Cochairs
Technical Report FS-01-04. Published by The AAAI Press, Menlo Park, California
This technical report is also available in book and CD format.
Please Note: Abstracts are linked to individual titles, and will appear in a separate browser window. Full-text versions of the papers are linked to the abstract text. Access to full text may be restricted to AAAI members. PDF file sizes may be large!
Contents
Using Uncertainty Within Computation / 1
Carla Gomes and Toby Walsh
Handling Uncertainty with Active Logic / 1
M. Anderson, M. Bhatia, P.Chi, W. Chong, D. Josyula, Y. Okamoto, D. Perlis, and K. Purang
Scheduling Contract Algorithms on Multiple Processors / 10
Daniel S. Bernstein, Theodore J. Perkins, Shlomo Zilberstein, and Lev Finkelstein
Formal Models of Heavy-Tailed Behavior in Combinatorial Search / 15
Hubie Chen, Carla Gomes, and Bart Selman
Randomizing Dispatch Scheduling Policies / 30
Vincent A. Cicirellos and Stephen F. Smith
Yet Another Local Search Method for Constraint Solving / 38
Philippe Codognet and Daniel Diaz
On Retaining Intermediate Probabilistic Models When Building Bayesian Networks / 47
Prashant J. Doshi, Lloyd G. Greenwald, and John R. Clarke
Optimal Schedules for Parallelizing Anytime Algorithms / 49
Lev Finkelstein, Shaul Markovitch, and Ehud Rivlin
First-Order Markov Decision Processes / 57
Matthew Greig
Two Algorithms for Learning the Parameters of Stochastic Context-Free Grammars / 58
Brent Heeringa and Tim Oates
A Bayesian Approach to Tackling Hard Computational Problems / 64
Eric Horvitz, Yongshao Ruan, Carla Gomes, Henry Kautz, Bart Selman, and Max Chickering
Selecting the Right Algorithm / 74
Michail G. Lagoudakis, Michael L. Littman, and Ronald E. Parr
Unrestricted Backtracking Algorithms for Satisfiability / 76
I. Lynce, L. Baptista, and J. Marques-Silva
Planning under Uncertainty via Stochastic Satisfiability / 83
Stephen M. Majercik
Reasoning across Scenarios in Planning under Uncertainty / 85
Peter McBurney and Simon Parsons
Temporal Update Mechanisms for Decision Making with Aging Observations in Probabilistic Networks / 93
Chilukuri K. Mohan, Kishan G. Mehrotra, and Pramod K. Varshney
Approximate and Compensate: A Method for Risk-Sensitive Meta-Deliberation and Continual Computation / 101
David C. Parkes and Lloyd G. Greenwald
Local Search and Backtracking vs. Non-Systematic Backtracking / 109
Steven Prestwich
Using Prior Knowledge with Adaptive Probing / 116
Wheeler Ruml
Methods for Sampling Pages Uniformly from the World Wide Web / 121
Paat Rusmevichientong, David M. Pennock, Steve Lawrence, and C. Lee Giles
Stochastic Constraint Programming / 129
Toby Walsh
Bayesian Networks for Logical Reasoning / 136
Jon Williamson
Modeling Unpredictable or Random Environments / 144
Jeannette M. Wing
Data Uncertainty in Constraint Programming: A Non-Probabilistic Approach / 146
Neil Yorke-Smith and Carmen Gervet