ACM Portal
  Subscribe (Full Service)    Register (Limited Service, Free)    Login
  Search:   The ACM Digital Library   The Guide
  
ACM Home Page
Please provide us with feedback. Feedback
The “lob-pass” problem and an on-line learning model of rational choice
Full text PdfPdf (766 KB)
Source Annual Workshop on Computational Learning Theory archive
Proceedings of the sixth annual conference on Computational learning theory table of contents
Santa Cruz, California, United States
Pages: 422 - 428  
Year of Publication: 1993
ISBN:0-89791-611-5
Authors
Naoki Abe
Jun-ichi Takeuchi
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 15,   Downloads (12 Months): 20,   Citation Count: 1
Additional Information:

references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/168304.168389
What is a DOI?

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
BF85
D.A. Berry and B. Ptistedt. Bandit Problems. Chapman and Hall, 1985.
 
Her90
Richard Herrnstein. Rational choice theory. American Ps!lchologist, 45(3):356-367, 1990.
 
HLL92
D. Helmbold, N. Littlestone, and P. Long. Apple tasting and nearly one-sided learning. In Proceedings of the ~6th A CM S~traposiura on the Theor~t of Computation, 1992.
 
KS90
M. Kearns and R. Schapire. Efficient distribution-free learning of probabilistic concepts. In Proceedings of IEEE Symposium on Foundations of Computer Science, 1990.
 
Lit88
Nick Littlestone, Learning Quickly When Irrelevant Attributes Abound: A New Linear-Threshold Algorithm, Machine Learning, v.2 n.4, p.285-318, April 1988  [doi>10.1023/A:1022869011914]
 
Ris86
Jorma Riasanen. Stochastic complexity and modeling. The Annals of Statistics, 14(3):1080 ll00, 1986.
 
Yam91
Kenji Yamanishi, A loss bound model for on-line stochastic prediction strategies, Proceedings of the fourth annual workshop on Computational learning theory, p.290-302, August 05-07, 1991, Santa Cruz, California, United States

CITED BY
Joe Kilian , Kevin J. Lang , Barak A. Pearlmutter, Playing the matching-shoulders lob-pass game with logarithmic regret, Proceedings of the seventh annual conference on Computational learning theory, p.159-164, July 12-15, 1994, New Brunswick, New Jersey, United States

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE

Additional Classification:
  F. Theory of Computation
  F.1 COMPUTATION BY ABSTRACT DEVICES
      F.1.2 Modes of Computation
          Subjects: Probabilistic computation

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING


General Terms:
Algorithms, Performance, Theory, Verification

Collaborative Colleagues:
Naoki Abe: colleagues
Jun-ichi Takeuchi: colleagues

The ACM Portal is published by the Association for Computing Machinery. Copyright © 2009 ACM, Inc.
Terms of Usage   Privacy Policy   Code of Ethics   Contact Us

Useful downloads: Adobe Acrobat    QuickTime    Windows Media Player    Real Player