Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person's assignment. Unlike our previous work of using genetic algorithms whose learning is implicit, the learning in both...

Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each...

We model deterrence with costly punishment when criminals have different abilities. Abilities are unobserved by both criminals and the courts. Based on past successes, criminals update their priors on being high-ability criminals. Courts cannot observe a criminal’s total past offenses. They do...