1.1k citations · 1.7k across the 7 of their papers we have counts for
7 papers
Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (1995)
Philippe Besnard, Steve Hanks
This is the Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, which was held in Montreal, QU, August 18-20, 1995
Temporal Reasoning About Uncertain Worlds
Steve Hanks
We present a program that manages a database of temporally scoped beliefs. The basic functionality of the system includes maintaining a network of constraints among time points, su…
A Probabilistic Model of Action for Least-Commitment Planning with Information Gather
Denise L. Draper, Steve Hanks, Daniel Weld
AI planning algorithms have addressed the problem of generating sequences of operators that achieve some input goal, usually assuming that the planning agent has perfect control ov…
Localized Partial Evaluation of Belief Networks
Denise L. Draper, Steve Hanks
Most algorithms for propagating evidence through belief networks have been exact and exhaustive: they produce an exact (point-valued) marginal probability for every node in the net…
Probabilistic Temporal Reasoning with Endogenous Change
Steve Hanks, David Madigan, Jonathan Gavrin
This paper presents a probabilistic model for reasoning about the state of a system as it changes over time, both due to exogenous and endogenous influences. Our target domain is a…
Decision-Theoretic Planning: Structural Assumptions and Computational Leverage
C. Boutilier, T. Dean, S. Hanks
Planning under uncertainty is a central problem in the study of automated sequential decision making, and has been addressed by researchers in many different fields, including AI p…