TY - GEN
T1 - Graph-based reasoning and reinforcement learning for improving Q/A performance in large knowledge-based systems
AU - Sharma, Abhishek
AU - Forbus, Kenneth D
PY - 2010/12/1
Y1 - 2010/12/1
N2 - Learning to plausibly reason with minimal user intervention could significantly improve knowledge acquisition. We describe how to integrate graph-based heuristic generalization, higher-order knowledge, and reinforcement learning to learn to produce plausible inferences with only small amounts of user training. Experiments on ResearchCyc KB contents show significant improvement in Q/A performance with high accuracy.
AB - Learning to plausibly reason with minimal user intervention could significantly improve knowledge acquisition. We describe how to integrate graph-based heuristic generalization, higher-order knowledge, and reinforcement learning to learn to produce plausible inferences with only small amounts of user training. Experiments on ResearchCyc KB contents show significant improvement in Q/A performance with high accuracy.
UR - http://www.scopus.com/inward/record.url?scp=79960133749&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79960133749&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:79960133749
SN - 9781577354840
T3 - AAAI Fall Symposium - Technical Report
SP - 96
EP - 101
BT - Commonsense Knowledge - Papers from the AAAI Fall Symposium, Technical Report
T2 - 2010 AAAI Fall Symposium
Y2 - 11 November 2010 through 13 November 2010
ER -