I would like to update the course literature on artificial intelligence. I am looking for some guide books for students which covers basic principles, mathematical description, explains the methods with examples and also gives advantages, drawbacks and limitations of the methodology.
Christian is right with both his recommendations. Additionally I would like to suggest C.M. Bishop's "Pattern Recognition and Machine Learning" if you are dealing with the math behind Bayesian approaches. Regarding your topics of interest, "Learning and Soft Computing" by Vojislav Kecman maybe is a promising book, too.
Get an eye on:
R. Keeney, H. Raiffa, Decision with multiple objectives: Preferences and value trade-offs, Cambridge & New York: Cambridge University Press, 1993.
Power D. J. (2002). Decision support systems: concepts and resources for managers. Westport, Conn., Quorum books.
Encyclopedia of Business Analytics and Optimization, IGI Global, ( 1st Edition). Editor: John Wang, 2014.
Raiffa, H., (1968): Decision Analysis. Introductory Lectures on Choices under Uncertainty, Addison-Wesley. (a classic book) H. Raiffa, Decision Analysis, New York: Addison-Wesley Reading Mass, 1968.
Y. Pavlov & R. Andreev, Decision control, management, and support in adaptive and complex systems: Quantitative models, Hershey, PA: IGI Global, 2013.
I agree completely with Christian and Benjamin. I still reference my 15yr old copy of Russel and Norvig every now and again.
It really depends quite how broad your AI course is.
"Bayesian Reasoning and Machine Learning" by David Barber is good for statistical models and clustering. It also has a free version online.
"Reinforcement Learning" by R. Sutton and A. Barto, is a bit old now but it's good for basics.
Artificial Intelligence: Foundations of Computational Agents
by David Poole, Alan Mackworth
Cambridge University Press 2010
ISBN/ASIN: 0521519004
ISBN-13: 9780521519007
Description:
A book about the science of artificial intelligence (AI). It presents artificial intelligence as the study of the design of intelligent computational agents. The book is structured as a textbook, but it is accessible to a wide audience of professionals and researchers.
This book is for in-depth analysis, dedicated to researchers and experts in "agents". After a general introduction, if the argument of the agents is your domain, I suggest you consider it.
I also recommend taking this course carried out by MIT Open Course
http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-034-artificial-intelligence-fall-2010/
Good research
You may follow the following link,
https://www.google.lk/search?q=good+text-books+on+artificial+intelligence&oq=good+text-books+on+artificial+intelligence&aqs=chrome..69i57j0j69i61.952j0j4&sourceid=chrome&es_sm=122&ie=UTF-8#q=good+text-books+on+artificial+intelligence&safe=off&tbm=bks
which provides a list of books on artificial intelligence
[1.] Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series), Kevin P. Murphy, 2012
[2.] Learning From Data, Yaser S. Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin, 2012
Dear all,
thank you for your contribution. I will order some of books already this week. If you lay your hands on some new literature in the field, please share your discovery.
Best regards, Lelde
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