Title: Dynamics of confined crowds modelled using Entropic Stochastic Resonance and Quantum Neural Networks
Authors: Vladimir G. Ivancevic, Darryn J. Reid
Addresses: Land Operations Division, Defence Science and Technology Organisation, P.O. Box 1500, 75 Labs, Edinburgh SA 5111, Australia. ' Land Operations Division, Defence Science and Technology Organisation, P.O. Box 1500, 75 Labs, Edinburgh SA 5111, Australia
Abstract: We present a new approach to modelling dynamics of confined crowds driven by Entropic Stochastic Resonance (ESR). The standard approach is to model confined Brownian particles using overdamped Langevin equations and corresponding linear, real-time, Fokker-Planck equations for Probability Density Functions (PDFs). Instead, we propose a new approach based on a set of (weakly or strongly) coupled Quantum Neural Networks (QNNs), which are self-organised, complex-valued nonlinear Schrodinger equations with unsupervised Hebbian-type learning. Utilising the full power of nonlinear analysis in the complex-plane, the new approach promises to be ideal for any kind of two-dimensional terrains. Besides, instead of over-simplistic Brownian particles, the new approach allows us to model crowds consisting of rigid-body-type agents.
Keywords: dynamics of confined crowds; ESR; entropic stochastic resonance; nonlinear Schrodinger equations; quantum neural networks; crowd modelling; dynamic modelling.
International Journal of Intelligent Defence Support Systems, 2009 Vol.2 No.4, pp.269 - 289
Published online: 02 Feb 2010 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article