Reinforcement Learning Rebirth, Techniques, Challenges, and Resolutions
نویسندگان
چکیده
منابع مشابه
The rebirth of children's learning.
Learning is a central part of children's lives, but the study of learning is a rather peripheral part of the field of cognitive development. Fortunately, this situation is starting to change; recent theoretical and methodological advances have sparked renewed interest in children's learning. This renewed interest has already yielded a set of consistent and interesting findings regarding how chi...
متن کاملApplying Online Search Techniques to Reinforcement Learning
In reinforcement learning it is frequently necessary to resort to an approximation to the true optimal value function. Here we investigate the bene ts of online search in such cases. We examine \local" searches, where the agent performs a nite-depth lookahead search, and \global" searches, where the agent performs a search for a trajectory all the way from the current state to a goal state. The...
متن کاملReinforcement Learning for Combining Relevance Feedback Techniques
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ignore the advantages of existing ones. In this paper, we propose an image relevance reinforcement learning (IRRL) model for integrating existing RF techniques. Various integration schemes are presented and a long-term shar...
متن کاملA Tutorial on Reinforcement Learning Techniques
Reinforcement Learning (RL) is learning through direct experimentation. It does not assume the existence of a teacher that provides examples upon which learning of a task takes place. Instead, in RL experience is the only teacher. With historical roots on the study of conditioned reflexes, RL soon attracted the interest of Engineers and Computer Scientists because of its theoretical relevance a...
متن کاملReinforcement learning, conditioning, and the brain: Successes and challenges.
The field of reinforcement learning has greatly influenced the neuroscientific study of conditioning. This article provides an introduction to reinforcement learning followed by an examination of the successes and challenges using reinforcement learning to understand the neural bases of conditioning. Successes reviewed include (1) the mapping of positive and negative prediction errors to the fi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: JOIV : International Journal on Informatics Visualization
سال: 2020
ISSN: 2549-9904,2549-9610
DOI: 10.30630/joiv.4.3.376