In machine learning, decision trees are employed extensively in solving classification problems. In order to design a decision tree classifier two main phases are employed. The fi...
Jason R. Beck, Maria Garcia, Mingyu Zhong, Michael...
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...
Modelling the geometry of organic forms using traditional CAD or animation tools is often difficult and tedious. Different models of morphogenesis have been successfully applied t...
Abstract. The paper introduces a reinforcement learning-based methodology for performance improvement of Intelligent Controllers. The translation interfaces of a 3-level Hierarchic...
We consider the problem of control traffic overhead in MANETs with long-lived connections, operating under a reactive routing protocol (e.g. AODV). In such settings, control traff...