{"id":262527,"date":"2026-07-13T19:05:54","date_gmt":"2026-07-13T16:05:54","guid":{"rendered":"https:\/\/1kitap1.com\/en\/handbook-on-decision-making-vol-1-chee-peng-lim\/"},"modified":"2026-07-13T19:05:54","modified_gmt":"2026-07-13T16:05:54","slug":"handbook-on-decision-making-vol-1-chee-peng-lim","status":"publish","type":"post","link":"https:\/\/1kitap1.com\/en\/handbook-on-decision-making-vol-1-chee-peng-lim\/","title":{"rendered":"Handbook On Decision Making Vol 1 – Chee Peng Lim"},"content":{"rendered":"
\"<\/figure>\n

Zheng, S.-Y. Cho, and C. Quek 26. Washington, R.: Incremental Markov-model planning. In: Proceedings of TAI 1996, Eighth IEEE International Conference on Tools With Artificial Intelligence (1996) 27. Hansen, E.A.: Solving POMDPs by searching in policy space. In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence (1998) 28. Hauskrecht, M.: Planning and control in stochastic domains with imperfect information. Massachusetts Institute of Technology (1997) 29. Ross, S., Pineau, J., Chaib-draa, B.: Theoretical Analysis of Heuristic Search Methods for Online POMDPs.<\/p>\n

Advances in Neural Information Processing Systems 20 (2008) 30. Smith, T., Simmons, R.G.: Point-Based POMDP Algorithms: Improved Analysis and Implementation. In: Proceedings of International Conference on Uncertainty in Artificial Intelligence (2005) 31. Spaan, M.T.J., Vlassis, N.: Perseus: Randomized point-based value iteration for POMDPs. Journal of Artificial Intelligence Research 24, 195\u2013220 (2005) 32.<\/p>\n

Pineau, J., Gordon, G., Thrun, S.: Anytime point-based approximations for large POMDPs. Journal of Artificial Intelligence Research 27, 335\u2013380 (2006) 33. Ji, S., et al.: Point-based policy iteration. In: Proceedings of the 22nd National Conference on Artificial Intelligence (2007) 34. Pineau, J., Gordon, G., Thrun, S.: Point-based value iteration: An anytime algorithm for POMDPs. In: Proceedings of International Joint Conference on Artificial Intelligence (2003) 35. Whitehead, S.D., Ballard, D.H.: Learning to perceive and act by trial and error. Machine Learning 7(1), 45\u201383 (1991) 36. Loch, J., Singh, S.: Using eligibility traces to find the best memoryless policy in partially observable Markov decision processes.<\/p>\n

In: Proceedings of the Fifteenth International Conference on Machine Learning. Morgan Kaufmann, San Francisco (1998) 37. Baird, L., Moore, A.: Gradient descent for general reinforcement learning. In: Advances in Neural Information Processing Systems, vol. 11. MIT Press, Cambridge (1999) 38. Chrisman, L.: Reinforcement learning with perceptual aliasing: The perceptual distinctions approach. In: Proceedings of the Tenth National Conference on Artificial Intelligence. AAAI Press, Menlo Park (1992) 39. Littman, M.L.: Memoryless policies: Theoretical limitations and practical results.<\/p>\n

In: From Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior. The MIT Press, Cambridge (1994) 40. Meuleau, N., et al.: Learning finite-state controllers for partially observable environments. In: Proceedings of the fifteenth conference on uncertainty in artificial intelligence. Morgan Kaufmann, San Francisco (1999) 41. Press, W.H., et al.: Numerical Recipes in C: the art of scientific computing, pp. 623\u2013 626.<\/p>\n

Cambridge University Press, Cambridge (1997) 42. Ron, D., Singer, Y.: The power of amnesia: learning probabilistic automata with variable memory length. Machine Learning (1996) 43. Shani, G., Brafman, R.I., Shimony, S.E.: Model-based online learning of POMDPs. In: Gama, J., Camacho, R., Brazdil, P.B., Jorge, A.M., Torgo, L. (eds.) ECML 2005. LNCS (LNAI), vol. 3720, pp. 353\u2013364. Springer, Heidelberg (2005) 44. McCallum, R.A.: Instance-based utile distinctions for reinforcement learning with hidden state.<\/p>\n

\n

Lakhmi C. Jain and Chee Peng Lim (Eds.) Handbook on Decision Making: Techniques and Applications Intelligent Systems Reference Library,Volume 4 Editors-in-Chief Prof. Janusz Kacprzyk Systems Research Institute Polish Academy of Sciences ul. Newelska 6 01-447 Warsaw Poland E-mail: kacprzyk@ibspan.waw.pl Prof. Lakhmi C. Jain University of South Australia Adelaide Mawson Lakes Campus South Australia 5095 Australia E-mail: Lakhmi.jain@unisa.edu.au Further volumes of this series can be found on our homepage: springer.com Vol. 1. Christine L. Mumford and Lakhmi C. Jain (Eds.)<\/p>\n

Computational Intelligence: Collaboration, Fusion and Emergence, 2009 ISBN 978-3-642-01798-8 Vol. 2.Yuehui Chen and Ajith Abraham Tree-Structure Based Hybrid Computational Intelligence, 2009 ISBN 978-3-642-04738-1 Vol. 3.Anthony Finn and Steve Scheding Developments and Challenges for Autonomous Unmanned Vehicles, 2010 ISBN 978-3-642-10703-0 Vol. 4. Lakhmi C. Jain and Chee Peng Lim (Eds.) Handbook on Decision Making: Techniques and Applications, 2010 ISBN 978-3-642-13638-2 Lakhmi C. Jain and Chee Peng Lim (Eds.) Handbook on Decision Making Vol 1: Techniques and Applications 123 Prof. Lakhmi C. Jain University of South Australia School of Electrical & Information Engineering KES Centre 5095 Adelaide South Australia Mawson Lakes Campus Australia E-mail: lakhmi.jain@unisa.edu.au Dr. Chee Peng Lim University of Science Malaysia School of Electrical and Electronic Engineering Engineering Campus 14300 Nibong Tebal, Penang Malaysia E-mail: cplim@eng.usm.my ISBN 978-3-642-13638-2 e-ISBN 978-3-642-13639-9 DOI 10.1007\/978-3-642-13639-9 Intelligent Systems Reference Library ISSN 1868-4394 Library of Congress Control Number: 2010928590 c\u20dd2010 Springer-Verlag Berlin Heidelberg This work is subject to copyright.<\/p>\n

All rights are reserved, whether the whole or part of the material is concerned, speci\ufb01cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on micro\ufb01lm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer.<\/p>\n

Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a speci\ufb01c statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.<\/p>\n

Typeset & Cover Design: Scienti\ufb01c Publishing Services Pvt. Ltd., Chennai, India.<\/p>\n<\/blockquote>\n

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.<\/em><\/p>\n

\n
\n

Table of Contents<\/p>\nToggle<\/span><\/path><\/svg><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n