Abstract This paper deals with automating the drawing of subway maps. There are two features of schematic subway maps that make them different from drawings of other networks such...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Planning algorithms have traditionally been geared toward achievement goals in single-agent environments. Such algorithms essentially produce plans to reach one of a specified se...
We introduce an alternative to the smoothing technique approach for constrained optimization. As it turns out for any given smoothing function there exists a modification with part...
Bipartite network flow problems naturally arise in applications such as selective assembly and preemptive scheduling. This paper presents fast algorithms for these problems that ...