Efficient reasoning

Many tasks require "reasoning"--i.e., deriving conclusions from a corpus of explicitly stored information--to solve their range of problems. An ideal reasoning system would produce all-and-only the correct answers to every possible query, produce answers that are as specific as possible, b...

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Veröffentlicht in:ACM computing surveys 2001-03, Vol.33 (1), p.1-30
Hauptverfasser: GREINER, Russell, DARKEN, Christian, SANTOSO, N. Iwan
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container_title ACM computing surveys
container_volume 33
creator GREINER, Russell
DARKEN, Christian
SANTOSO, N. Iwan
description Many tasks require "reasoning"--i.e., deriving conclusions from a corpus of explicitly stored information--to solve their range of problems. An ideal reasoning system would produce all-and-only the correct answers to every possible query, produce answers that are as specific as possible, be expressive enough to permit any possible fact to be stored and any possible query to be asked, and be (time) efficient. Unfortunately, this is provably impossible: as correct and precise systems become more expressive, they can become increasingly inefficient, or even undecidable. This survey first formalizes these hardness results, in the context of both logic- and probability-based reasoning, then overviews the techniques now used to address, or at least side-step, this dilemma.
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source ACM Digital Library Complete
subjects Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Artificial intelligence
Computer programming
Computer science
control theory
systems
Efficiency
Exact sciences and technology
Information management
Knowledge-based systems
Learning and adaptive systems
Logic
Management
Reasoning
Studies
System design
Systems analysis
Theoretical computing
title Efficient reasoning
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