By Steffen Jorgensen, Marc Quincampoix, Thomas L. Vincent

ISBN-10: 0817643990

ISBN-13: 9780817643997

ISBN-10: 0817645535

ISBN-13: 9780817645533

This selection of chosen contributions provides an account of contemporary advancements in dynamic online game concept and its functions, overlaying either theoretical advances and new functions of dynamic video games in such parts as pursuit-evasion video games, ecology, and economics. Written through specialists of their respective disciplines, the chapters are an outgrowth of shows from the eleventh overseas Symposium on Dynamic video games and Applications.

Key issues lined include:

* stochastic and differential games

* dynamic video games and their purposes in a variety of components, reminiscent of ecology and economics

* numerical tools and algorithms in dynamic games

* 0- and nonzero-sum games

* pursuit-evasion games

* evolutionary video game conception and applications

The paintings will function a state-of-the paintings account of modern advances in dynamic video game conception and its functions for researchers, practitioners, and complex scholars in utilized arithmetic, mathematical finance, and engineering.

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Read Online or Download Advances in Dynamic Game Theory: Numerical Methods, Algorithms, and Applications to Ecology and Economics PDF

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Extra info for Advances in Dynamic Game Theory: Numerical Methods, Algorithms, and Applications to Ecology and Economics

Sample text

Saint-Pierre P. Non linear Impulse Target Problems under State Constraint: A Numerical Analysis based on Viability Theory. Set-Valued Analysis. Set-Valued Analysis. 12, no. 4, 383–416 (2004). [32] Da Prato G. & Frankowska H. A stochastic Filippov Theorem, Stochastic Calculus 12, 409–426 (1994). [33] Doyen L. & Seube N. Control of uncertain systems under bounded chattering. Dynam. Control 8, no. 2, 163–176 (1998). C. E. Differential games and representation formulas for solutions of Hamilton-Jacobi Equations Indiana Univ.

Hybrid Kernels and Capture Basins for Impulse Constrained Systems, Proceedings of Hybrid Systems (2003). [62] Saint-Pierre P. The Guaranteed Hybrid Kernel Algorithm applied to evaluate barrier options in Finance, Proceeding MTNS04 (2004). [63] Saint-Pierre P. Viable capture basin for studying differential and hybrid games: application to finance. Int. Game Theory Rev. 6, no. 1, 109–136 (2004). [64] Saint-Pierre P. Approximation of capture basins for hybrid systems, in Proceedings of the 2001 European Control Conference, Porto, Portugal, September 4–7 (2001).

The palikinesia function which indicates the maximal level of risk under which viability can be maintained is defined by ψ(x, u, v) := inf sup esssupt>0 v (t) , β u(·)∈U (34) where the infimum is over the strategies β ensuring the viability. Proposition 25. The hypograph of the palikinesia function is the discriminating kernel associated with the following system:  (i) x (t) = (u(t) − v(t))x(t)    (ii) u (t) ∈ B(0, |z|) (35) (iii) v (t) ∈ B(0, d)    (iv) z (t) = 0 subjected to the viability constraints u(t) ∈ R and C γ x(t)−|z| ≤ v(t) ≤ v.

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Advances in Dynamic Game Theory: Numerical Methods, Algorithms, and Applications to Ecology and Economics by Steffen Jorgensen, Marc Quincampoix, Thomas L. Vincent

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