—Reinforcement learning is the scheme for unsupervised learning in which robots are expected to acquire behavior skills through self-explorations based on reward signals. There a...
Hiroaki Arie, Tetsuya Ogata, Jun Tani, Shigeki Sug...
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
Although the ant metaphor has been successfully applied to routing of data packets both in wireless and fixed networks, little is known yet about its appropriateness for search i...
Abstract--We consider the design of multiple-input multipleoutput communication systems with a linear precoder at the transmitter, zero-forcing decision feedback equalization (ZFDF...
In mobile wireless networks, dynamic allocation of resources such as transmit powers, bit-rates, and antenna beams based on the channel state information of mobile users is known t...