RT Journal Article
T1 Quantum speedup for active learning agents
A1 Paparo, Giuseppe Davide
A1 Dunjko, Vedran
A1 Makmal, Adi
A1 Martín-Delgado Alcántara, Miguel Ángel
A1 Briegel, Hans J.
AB Can quantum mechanics help us build intelligent learning agents? A defining signature of intelligent behavior is the capacity to learn from experience. However, a major bottleneck for agents to learn in reallife situations is the size and complexity of the corresponding task environment. Even in a moderately realistic environment, it may simply take too long to rationally respond to a given situation. If the environment is impatient, allowing only a certain time for a response, an agent may then be unable to cope with the situation and to learn at all. Here, we show that quantum physics can help and provide a quadratic speedup for active learning as a genuine problem of artificial intelligence. This result will be particularly relevant for applications involving complex task environments.
PB American Physical Society (APS)
SN 2160-3308
YR 2014
FD 2014-06-08
LK https://hdl.handle.net/20.500.14352/35595
UL https://hdl.handle.net/20.500.14352/35595
LA eng
NO ©2014 American Physical Society. M. A. M.-D. acknowledges support by the Spanish MICINN Grants No. FIS2009-10061 and No. FIS2012- 33152, the CAM Research Consortium QUITEMAD S2009-ESP-1594, the European Commission PICC: FP7 2007-2013, Grant No. 249958, and the UCM-BS Grant No. GICC-910758. H. J. B. acknowledges support by the Austrian Science Fund (FWF) through the SFB FoQuS F 4012, and the Templeton World Charity Fund grant TWCF0078/AB46. G. D. P. and V. D. have contributed equally to this work.
NO Unión Europea. FP7
NO Ministerio de Ciencia e Innovación (MICINN)
NO Comunidad de Madrid
NO Universidad Complutense de Madrid/Banco de Santander
NO Austrian Science Fund (FWF)
NO Templeton World Charity Fund
DS Docta Complutense
RD 9 abr 2025