RL4HCI: Reinforcement Learning for Humans, Computers, and Interaction

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 ...

Reinforcement learning (RL) is an area of machine learning that is concerned with how an agent learns to make decisions sequentially in order to optimize a particular performance measure. For achieving such a goal, the agent has to choose either 1) ...

• 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 ...