The Interval Reduction Strategy for Monitoring Cupcake Problems

Monitoring is the process by which agents assess their environments. Most AI applications rely on periodic monitoring, but for a large class of problems this is ine cient. The interval reduction monitoring strategy is better. It also appears in humans and arti cial agents when they are given the same set of monitoring problems. We implemented two genetic algorithms to evolve monitoring strategies and a dynamic programming algorithm to nd an optimum strategy. We also developed a simple mathematical model of monitoring. We tested all these strategies in simulations, and we tested human strategies in a \video game." Interval reduction always emerged. Environmental factors such as error and monitoring costs had the same qualitative e ects on the strategies, irrespective of their genesis. Interval reduction appears to be a general monitoring strategy.