Uncertainty in Artificial Intelligence
First Name   Last Name   Password   Forgot Password   Log in!
    Proceedings         Authors   Author's Info   Article details         Search    
Reasoning, Metareasoning, and Mathematical Truth: Studies of Theorem Proving under Limited Resources
Eric Horvitz, Adrian Klein
Abstract:
In earlier work, we introduced flexible inference and decision-theoretic metareasoning to address the intractability of normative inference. Here, rather than pursuing the task of computing beliefs and actions with decision models composed of distinctions about uncertain events, we examine methods for inferring beliefs about mathematical truth before an automated theorem prover completes a proof. We employ a Bayesian analysis to update belief in truth, given theorem-proving progress, and show how decision-theoretic methods can be used to determine the value of continuing to deliberate versus taking immediate action in time-critical situations.
Keywords: Theorem proving, time-critical reasoning, Bayesian methods, decision making under bo
Pages: 306-314
PS Link: http://www.research.microsoft.com/research/dtg/horvitz/TRUTH.HTM
PDF Link: /papers/95/p306-horvitz.pdf
BibTex:
@INPROCEEDINGS{Horvitz95,
AUTHOR = "Eric Horvitz and Adrian Klein",
TITLE = "Reasoning, Metareasoning, and Mathematical Truth: Studies of Theorem Proving under Limited Resources",
BOOKTITLE = "Proceedings of the Eleventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-95)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1995",
PAGES = "306--314"
}


hosted by DSL   •   site info   •   help