2003
DOI: 10.1007/978-94-017-0317-8
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Intelligent Control of Robotic Systems

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Cited by 17 publications
(11 citation statements)
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References 208 publications
(299 reference statements)
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“…The above conceptual equation gave rise to a series of population models. The simplest continuous-time model, due to Thomas Malthus from 1798 [Mal798], 25 has no migration, while the birth and death terms are proportional to x,ẋ (1.23) where b, d are positive constants and x 0 = x(0) is the initial population. Thus, according to the Malthus model (1.23), if b > d, the population grows exponentially, while if b < d, it dies out.…”
Section: Lord Robert May: Population Modelling and Chaosmentioning
confidence: 99%
See 1 more Smart Citation
“…The above conceptual equation gave rise to a series of population models. The simplest continuous-time model, due to Thomas Malthus from 1798 [Mal798], 25 has no migration, while the birth and death terms are proportional to x,ẋ (1.23) where b, d are positive constants and x 0 = x(0) is the initial population. Thus, according to the Malthus model (1.23), if b > d, the population grows exponentially, while if b < d, it dies out.…”
Section: Lord Robert May: Population Modelling and Chaosmentioning
confidence: 99%
“…Clearly, this approach is fairly oversimplified and apparently fairly unrealistic. (However, if we consider the past 25 The Rev. Thomas Robert Malthus, FRS (February, 1766-December 23, 1834), was an English demographer and political economist best known for his pessimistic but highly influential views.…”
Section: Lord Robert May: Population Modelling and Chaosmentioning
confidence: 99%
“…A general form of a driven, non-conservative Hamilton's equations reads: 25) where F i = F i (t, q, p) represent any kind of joint-driving covariant torques, including active neuro-muscular-like controls, as functions of time, angles and momenta, as well as passive dissipative and elastic joint torques. In the covariant momentum formulation (3.24), the non-conservative Hamilton's equations (3.25) becomė…”
Section: Hamiltonian Geometry In Human-like Biomechanicsmentioning
confidence: 99%
“…In particular, multiplex networks (the sub-class of multi-layer networks where nodes are the same on all layers) found applications in technological [3][4][5], biological [6], and social systems [7,8], as well as in human brain, artificial intelligence and robotics [9,10]. Multiplex networks are furthermore useful tools for the analysis of climatological data, e.g.…”
Section: Introductionmentioning
confidence: 99%