An Approach for Creation of Logistics Management System for Food Banks Based on Reinforcement Learning

Recent advancements in reinforcement learning confirm that reinforcement learning techniques can solve large scale problems leading to high quality autonomous decision making. It is a matter of time until we will see large scale applications of ...

In speedup-learning problems, where full descriptions of operators are known, both explanation-based learning (EBL) and reinforcement learning (RL) methods can be applied. This paper shows that both methods involve fundamentally the same process of ...

• RL can be used to solve problems involving sequential decision-making.
• RL is based on trial-and-error learning through rewards and punishments.
• The ultimate goal of an RL agent is to maximize cumulative reward.
• RL agent tries ...

Reinforcement Learning (RL) is a machine learning (ML) technique to learn sequential decision-making in complex problems. RL is inspired by trial-and-error based human/animal learning. It can learn an optimal policy autonomously with knowledge ...