A Hybrid Simulation and Reinforcement Learning Algorithm for Enhancing Efficiency in Warehouse Operations
The use of simulation and reinforcement learning can be viewed as a flexible approach to
aid managerial decision-making, particularly in the face of growing complexity in …
aid managerial decision-making, particularly in the face of growing complexity in …
Body calibration: Automatic inter-task mapping between multi-legged robots with different embodiments in transfer reinforcement learning
S Ikeda, H Kono, K Watanabe, H Suzuki - Actuators, 2022 - mdpi.com
Machine learning algorithms are effective in realizing the programming of robots that behave
autonomously for various tasks. For example, reinforcement learning (RL) does not require …
autonomously for various tasks. For example, reinforcement learning (RL) does not require …
Autonomous Reusing Policy Selection Using Spreading Activation Model in Deep Reinforcement Learning
This paper describes a policy transfer method of a reinforcement learning agent based on
the spreading activation model of cognitive psychology. This method has a prospect of …
the spreading activation model of cognitive psychology. This method has a prospect of …