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Hill Climbing
Inductive Learning
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Search Strategy
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Mio: User's Manual
Mio: User's Manual,Lourdes Pena Castillo
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Mio: User's Manual
(
Citations: 1
)
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Lourdes Pena Castillo
Mio is an example-driven multirelational
learning system
which performs a top-down search in the subsumption lattice, which is
lower bound
by a bottom clause. This bottom clause is constructed by inverse entailment. Three search strategies are included in Mio: IDA*, beam-search and hill-climbing. In addition, Mio supports the use of macro-operators [2, 5] and is able to perform parallel search [3] and active
inductive learning
[4]. This manual explains how to use Mio but not the research results behind it; for information about macros, parallel search, active
inductive learning
and experiments performed with Mio the reader is referred to [1].
Cumulative
Annual
References
(5)
Macro-Operators in Multirelational Learning: A Search-Space Reduction Technique
(
Citations: 6
)
Lourdes Peña Castillo
,
Stefan Wrobel
Conference:
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECML
, pp. 357-368, 2002
On the Stability of Example-Driven Learning Systems: A Case Study in Multirelational Learning
(
Citations: 8
)
Lourdes Peña Castillo
,
Stefan Wrobel
Conference:
Mexican International Conference on Artificial Intelligence - MICAI
, pp. 321-330, 2002
A comparative study on methods for reducing myopia of hill-climbing search in multirelational learning
(
Citations: 9
)
Lourdes Peña Castillo
,
Stefan Wrobel
Conference:
International Conference on Machine Learning - ICML
, 2004
Learning Minesweeper with Multirelational Learning
(
Citations: 4
)
Lourdes Peña Castillo
,
Stefan Wrobel
Conference:
International Joint Conference on Artificial Intelligence - IJCAI
, pp. 533-540, 2003
Search Improvements in Multirelational Learning
(
Citations: 2
)
Unknown
Published in 2004.
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Citations
(1)
SHARP: A shape recognition system and its parallel implementation
(
Citations: 2
)
C. P. Ravikumar
,
Rajender Sethi
Journal:
Microprocessors and Microsystems
, vol. 19, no. 3, pp. 131-138, 1995