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Error-driven learning

Error-driven learning is a sub-area of machine learning concerned with how an agent ought to take actions in an environment so as to minimize some… 
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GeneRecIntelligent agentLeabraMachine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Evidence of error-driven cross-situational word learning
One powerful way children can learn word meanings is via cross-situational learning, the ability to discern consistent word… 
2017
2017
How does of initial inaccuracy benefit cross-situational word learning?
The 39th Annual Meeting of the Cognitive Science Society (CogSci 2017) (London, UK, 26-29 July 2017) 
2011
2011
An approach for discovering Multilingual news events and term association from the Web
We have investigated an approach for automatically discovering news events from Web online news downloaded from different sites… 
2007
2007
Automatic Spelling Correction Rule Extraction and Application for Spoken-Style Korean Text
Nowadays, spoken-style text is prevailing because lots of information are being written in spoken-style such as Short-Message… 
2007
2007
Recognizing the Extent of Chinese Time Expressions Based on the Dependency Parsing and Error-Driven Learning
Recognizing time expressions is the foundation of its normalization,and its performance directly influences the robustness of the… 
2006
2006
Chunk Parsing Based on SVM and Error-Driven Learning Methods
Chunk parsing of Chinese texts can decrease the difficulty of syntactic parsing.This paper proposes a chunking approach that… 
2006
2006
A New Error-driven Learning Approach for Chinese Word Segmentation
A well known problem for Chinese word segmentation(CWS)is that we can not have a unique definition of words.Different standards… 
2005
2005
Applying transformation-based error-driven learning to structured natural language queries
XML information retrieval (XML-IR) systems aim to provide users with highly exhaustive and highly specific results. To interact… 
2004
2004
From mind in the mouth to language in the mind Language in Mind edited by D. Gentner and S. Goldin-Meadow, MIT Press, 2003. £22.95 (522 pages) ISBN 0 262 57163 3
2002
2002
BIOANT A Biologically Plausible Connectionist Approach to an Insect Simulation
The system BIOANT is designed to demonstrate the use of a biologically plausible artificial neural network in a system that… 
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