| Budget Amount *help |
¥14,300,000 (Direct Cost: ¥11,000,000、Indirect Cost: ¥3,300,000)
Fiscal Year 2014: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2013: ¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2012: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2011: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
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| Outline of Final Research Achievements |
Online decision making is a process where decision making and data observation are repeated. It is widely recognized that, for various problems of decision making, convex optimization theory gives a general framework of design and analysis of algorithms. However, it is limited to those problems where the domains or the decision spaces are continuous. In this study, we extend the theory so that it can be uniformly applied to a wide class of discrete domains such as rankings, spanning trees and a set of satisfying assignments. Furthermore, we consider a generalized problem where the cost of decision making for each trial depends on the past decisions made so far, and give a condition under which the problem has an efficient and high performing algorithm.
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