Abstract. Research on practical models of autonomous agents has largely focused on a procedural view of goal achievement. This allows for efficient implementations, but prevents an...
The standard approach in feedback control systems is to sample and control periodically. For some applications, such as networked control systems or severely energy-constrained sys...
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
Conventional mission-critical systems cannot prevent mission failure in dynamic battlefield environments in which the execution situations or missions change abruptly. To solve th...
Sangsoo Kim, Jiyong Park, Heeseo Chae, Hoh Peter I...
For difficult prediction problems, practitioners often segment the data into relatively homogenous groups and then build a model for each group. This two-step procedure usually res...