Optimal selection of information with restricted storage capacity

• Published in: Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181) Vol. 4; pp. 2285 - 2288 vol.4
• Main Author: Pronzato, L.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 1998
• Subjects: Additives; Binary search trees; Delay; Feedback; Markov processes; Random variables; Stochastic processes
• DOI: 10.1109/ICASSP.1998.681605
• EISSN: 2379-190X
• ISBN: 9780780344280; 0780344286
• ISSN: 1520-6149

We consider the situation where n items have to be selected among a series of N presented sequentially, the information contained in each item being random. The problem is to get a collection of n items with maximal information. We consider the case where the information is additive, and thus need to maximize the sum of n independently identically distributed random variables x/sub k/ observed sequentially in a sequence of length N. This is a stochastic dynamic-programming problem, the optimal solution of which is derived when the distribution of the x/sub k/s is known. The asymptotic behaviour of this optimal solution (when N tends to infinity with n fixed) is considered. A (forced) certainty-equivalence policy is proposed for the case where the distribution is unknown and estimated on-line.