Download Advanced Intelligent Computing Theories and Applications. by De-Shuang Huang, Laurent Heutte, Marco Loog PDF

By De-Shuang Huang, Laurent Heutte, Marco Loog

This e-book - at the side of the 2 volumes LNCS 4681 and LNAI 4682 - constitutes the refereed lawsuits of the 3rd foreign convention on clever Computing, ICIC 2007, held in Qingdao, China in August 2007. The clever computing know-how features a variety of suggestions akin to synthetic intelligence, perceptual and development reputation, evolutionary and adaptive computing, informatics theories and functions, computational neuroscience and bioscience, tender computing, case established and limited reasoning, brokers, networking and machine supported co-operative operating, human laptop interface concerns. ICIC subject matter unifies the image of latest clever computing concepts as an essential idea that highlights the traits in complicated computational intelligence and bridges theoretical study with purposes.

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S. Huang, L. Heutte, and M. ): ICIC 2007, CCIS 2, pp. 11–20, 2007. -P. -S. -Y. Lin algorithm merges the advantage of variable vigilance value of the ART and the pruning mechanism of the GAR (Grow and Represent Model) [9] theorem, amending the disadvantage of the boxes method which maps only one activated box for each input vector. It dynamically adjusts the size and location of the sensitivity region for activated neurons, and makes boundaries between categories to be changeable, resulting in producing more suitable input for increasing the system learning speed.

By Lemma 3, in order to show that the equilibrium z ∗ of System (1) is delay-independent asymptotical stability, we need prove the following two conditions 1) −E + T is a Hurwitz matrix; 2) det(G(jω, τ )) = 0 for any ω ∈ IR and any τ ≥ 0. Let λ be an arbitrary eigenvalue of the matrix −E + T , this implies that λ + 1 is an eigenvalue of the matrix T . By Lemma 1 and the assumption of Theorem 1, we have |λ + 1| ≤ ||T ||∞ < 1 . This shows that the real part of the complex number λ is negative, that is, −E + T is a Hurwitz matrix, Condition 1) holds.

Q is updated according to equation (7). 1 Cart-Pole Simulation The well-known cart-pole simulation having been used in verification of the performance of reinforcement learning algorithms is simulated here to check if the proposed architecture works. A typical mathematical model of a cart-pole system can be represented by forms as (8) and (9). We use fourth order Runge-Kutta to simulate the cart-pole model by a personal computer [10]. -P. -S. -Y. Lin xt = Ft + ml[θ t2 sin θ t − θ t cos θ t ] − µ c sgn( xt ) ..

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