Learning and control in virtual reality for machine intelligence
Date of Original Version
This paper presents a Virtual Reality (VR) interactive platform for learning and control for machine intelligence based on Adaptive Dynamic Programming (ADP). Recent research results have provided strong evidences that ADP could be a key technique for brain-like intelligent systems design, and VR is a powerful human-computer interface which can provide a three-dimensional (3D) active virtual environment. Converge these two subjects, we design an interactive system to facilitate and demonstrate the learning and control in VR environment with ADP. Our main goal in this paper is two-fold. First, we demonstrate that VR could be a useful platform to demonstrate and visualize machine intelligence research through the simulated 3D environment. Second, the integration of VR into machine intelligence research can provide a powerful platform to simulate, validate and facilitate the real-time interaction between the intelligent system and an unstructured environment. We discuss the detailed design strategy of the VR platform, and also demonstrated the interactive system performance based on the triple link inverted pendulum benchmark. © 2012 IEEE.
ICICIP 2012 - 2012 3rd International Conference on Intelligent Control and Information Processing
Fang, Xiao, Haibo He, Zhen Ni, and Yufei Tang. "Learning and control in virtual reality for machine intelligence." ICICIP 2012 - 2012 3rd International Conference on Intelligent Control and Information Processing , (2012): 63-67. doi:10.1109/ICICIP.2012.6391478.