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pro vyhledávání: '"Li, JR"'
Autor:
Zhang, Wei, Li, Jr-Shin
Interest in reinforcement learning (RL) for massive-scale systems consisting of large populations of intelligent agents interacting with heterogeneous environments has witnessed a significant surge in recent years across diverse scientific domains. H
Externí odkaz:
http://arxiv.org/abs/2409.15737
We present a computational method for open-loop minimum-norm control synthesis for fixed-endpoint transfer of bilinear ensemble systems that are indexed by two continuously varying parameters. We suppose that one ensemble parameter scales the homogen
Externí odkaz:
http://arxiv.org/abs/2403.18131
Ensemble systems, pervasive in diverse scientific and engineering domains, pose challenges to existing control methods due to their massive scale and underactuated nature. This paper presents a dynamic moment approach to addressing theoretical and co
Externí odkaz:
http://arxiv.org/abs/2401.01770
In complex networks, interactions between multiple agents give rise to an array of intricate global dynamics, ranging from synchronization to cluster formations. Decoding the connectivity structure as well as the types of interactions from measuremen
Externí odkaz:
http://arxiv.org/abs/2310.15990
Autor:
Zhang, Wei, Li, Jr-Shin
Koopman operators, since introduced by the French-born American mathematician Bernard Koopman in 1931, have been employed as a powerful tool for research in various scientific domains, such as ergodic theory, probability theory, geometry, and topolog
Externí odkaz:
http://arxiv.org/abs/2211.07112
Autor:
Zhang, Wei, Li, Jr-Shin
Ensemble control, an emerging research field focusing on the study of large populations of dynamical systems, has demonstrated great potential in numerous scientific and practical applications. Striking examples include pulse design for exciting spin
Externí odkaz:
http://arxiv.org/abs/2211.02975
In the study of induced bilinear systems, the classical Lie algebra rank condition (LARC) is known to be impractical since it requires computing the rank everywhere. On the other hand, the transitive Lie algebra condition, while more commonly used, r
Externí odkaz:
http://arxiv.org/abs/2203.07483
In this paper, we study the problem of learning dynamical properties of ensemble systems from their collective behaviors using statistical approaches in reproducing kernel Hilbert space (RKHS). Specifically, we provide a framework to identify and clu
Externí odkaz:
http://arxiv.org/abs/2112.14307
In this paper, we study uniform ensemble controllability (UEC) of linear ensemble systems defined in an infinite-dimensional space through finite-dimensional settings. Specifically, with the help of the Stone-Weierstrass theorem for modules, we provi
Externí odkaz:
http://arxiv.org/abs/2112.14301
The reservoir computing networks (RCNs) have been successfully employed as a tool in learning and complex decision-making tasks. Despite their efficiency and low training cost, practical applications of RCNs rely heavily on empirical design. In this
Externí odkaz:
http://arxiv.org/abs/2112.06891