In our previous research we suggested an approach to maximizing agents preferences over schedules of multiple tasks with temporal and precedence constraints. The proposed approach...
A team of agents planning to perform a complex task make a number of interrelated decisions as they determine precisely how that complex task will be performed. The decision set i...
While genetically inspired approaches to multi-objective optimization have many advantages over conventional approaches, they do not explicitly exploit directional/gradient informa...
Bayesian statistical theory is a convenient way of taking a priori information into consideration when inference is made from images. In Bayesian image detection, the a priori dist...
Design problems involve issues of stylistic preference and flexible standards of success; human designers often proceed by intuition and are unaware of following any strict rule-b...