Generating three binary addition algorithms using reinforcement programming

• 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 ...

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 ...

This report discusses the behavioural learning properties of a musical agent learning to generate a two-part counterpoint using SARSA , one of the on-policy temporal difference learning approaches. The policy was learned using hand-crafted rules ...