An autonomous mobile robot based on quantum algorithm

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3801 LNAI, Issue , 2005, Pages 393-398

  Dong, Daoyi ^a   Chen, Chunlin ^a   Zhang, Chenbin ^a   Chen, Zonghai ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; HYBRID SENSORS; LEARNING SYSTEMS; SQUIDS;

QUANTUM HALL SENSORS; QUANTUM REINFORCEMENT LEARNING (QRL) ALGORITHMS; QUANTUM SENSORS;

MOBILE ROBOTS;

EID: 33646837341     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11596448_57     Document Type: Conference Paper

References (6)

1. Morisawa, J., Otaka, M., Kodama, M., Kato, T., Suzuki, S.: Detection of Intergranular Cracking Susceptibility Due to Hydrogen in Irradiated Austenitic Stainless Steel with A Superconducting Quantum Interference Device (SQUID) Sensor. J. Nucl. Mater. 302 (2002) 66-71
2. 0.8Sb Quantum Well Hall Effect Sensors. Sensors and Actuators. 81 (2000) 13-17
3. Behet, M., Das, J., De Boeck, J., Borghs, G.: InAs/(Al, Ga)Sb Quantum Well Structure for Magnetic Sensors. IEEE Trans. Magn. 34 (1998) 1300-1302
4. Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information. Cambridge University Press, Cambridge, England (2000)
5. Dong, D. Y., Chen, C.L., Chen, Z.H.: Quantum Reinforcement Learning. In: Wang, L., Chen, K., Ong, Y.S. (eds.): Advances in Natural Computation. Lecture Notes in Computer Science, Vol. 3611. Springer-Verlag, GmbH (2005) 686-689
6. Sutton, R., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge, MA (1998)