Consideration is given to a new generalized version of the familiar best-choice problem, related to the well-known collective-choice-theory conception of choice function. Certain classes of stopping rules are introduced, and the probability of selecting one of the best (with respect to a given choice function) alternatives is estimated. This work is an approach to choice theory from the viewpoint of statistical sequential analysis.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence