Frequent requirement changes are a major point of concern in today's scenario. As a
solution to such issues, agile software development (ASD) has efficiently replaced the …

This paper aims to introduce nonlinear optimization in the fuzzy reinforcement learning (RL)
approach through genetic algorithm (GA)-based minimization. In conventional fuzzy RL, an …

Effectiveness and efficiency of manufacturing depends on the manufacturing equipment.
Timely detection and diagnosis of abnormal operating conditions of equipment and further …

Reinforcement learning (RL) is a subfield of Artificial intelligence concerned with how agents
are trained to become intelligent, so as to take optimum actions in a stochastic environment …

Climate change due to air pollution and emission of greenhouse gases are affecting the
flora and fauna drastically. Fuel-based transportation is one of the biggest causes of this …

Reinforcement learning, which is learning by itself, finds its application in almost all sort of
field including stock market, medical field, engineering field and forecasting. Control …