Adaptive Hybrid Synchronization Primitives: A Reinforcement Learning Approach
نویسندگان
چکیده
منابع مشابه
Recurrent Reinforcement Learning: A Hybrid Approach
Successful applications of reinforcement learning in real-world problems often require dealing with partially observable states. It is in general very challenging to construct and infer hidden states as they often depend on the agent’s entire interaction history and may require substantial domain knowledge. In this work, we investigate a deep-learning approach to learning the representation of ...
متن کاملHierarchical Reinforcement Learning: A Hybrid Approach
In this thesis we investigate the relationships between the symbolic and subsymbolic methods used for controlling agents by artificial intelligence, focusing in particular on methods that learn. In light of the strengths and weaknesses of each approach, we propose a hybridisation of symbolic and subsymbolic methods to capitalise on the best features of each. We implement such a hybrid system, c...
متن کاملReinforcement Learning for Motor Primitives
Humans demonstrate a large variety of very complicated motor skills in their day-to-day life. Their agility and adaptability to new control task remains unmatched by the millions of robots laboring on factory floors and roaming research labs. Achieving the abilities of learning and improving new motor skills has become an essential component in order to get a step closer to human-like motor ski...
متن کاملOne-sided Synchronization A new Approach to Synchronization Primitives
Todays operating systems are designed to manage multiple processes within a uniprocessor system, within several processors and even within distributed computer systems. Fundamental to this design is concurrency, especially synchronization of the activities of multiple processes. Most books on operating systems contain large chapters for this important topic. All discussed techniques therein are...
متن کاملReinforcement Learning for Parameterized Motor Primitives [IJCNN1759]
One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the “building blocks of movement generation”, called motor primitives. Motor primitives, as used in this paper, are parameterized control policies such as splines or nonlinear differential equations with desired attractor properties. While a lot of progress has been mad...
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: International Journal of Advanced Computer Science and Applications
سال: 2020
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2020.0110508