Sequential Selection Procedures--A Decision Theoretic Approach

Evaluating a Decision-Theoretic Approach to Tailored Example Selection

We present the formal evaluation of a framework that helps students learn from analogical problem solving, i.e., from problem-solving activities that involve worked-out examples. The framework incorporates an innovative example-selection mechanism, which tailors the choice of example to a given student so as to trigger studying behaviors that are known to foster learning. This involves a two-ph...

Automata-Theoretic Decision Procedures for Information Logics

Optimal sequential procedures with Bayes decision rules

In this article, a general problem of sequential statistical inference for general discrete-time stochastic processes is considered. The problem is to minimize an average sample number given that Bayesian risk due to incorrect decision does not exceed some given bound. We characterize the form of optimal sequential stopping rules in this problem. In particular, we have a characterization of the...

A Bayesian Randomized Clinical Trial: A Decision Theoretic Sequential Design

We propose a Bayesian decision theoretic framework for randomization in clinical trials. The proposed approach reconciles the apparent contradiction between the practice of clinical trial design and implications of a traditional decision theoretic setup. Although it is universal practice to use randomization in clinical trial design, a standard decision theoretic setup does not justify randomiz...

A Sequential Selection Processin Group Decision

In this paper a Sequential Selection Process in Group Decision Making under linguistic assessments is presented, where a set of linguistic preference relations represents individuals preferences. A collective linguistic preference is obtained by means of a deened linguistic ordered weighted averaging operator whose weights are chosen according to the concept of fuzzy majority, speciied by a fuz...