Dynamic, Genetic and Chaotic Programming

Partial table of contents: DYNAMIC NEURAL NETWORKS VERSUS AUTOMATED KNOWLEDGE ACQUISITION. Paradigm/Problem Matching (B. Soucek). Dynamic Systems Control via Associative Reinforcement Learning (V. Gullapalli). Recognition and Restoration of Periodic Signals with Time-Dependent Neural Network (R. Kamimura). Adaptive Stack Filtering by LMS and Perceptron Learning (N. Ansari & Y. Huang). Managing the Traffic of a Satellite Communication Network by Neural Network (N. Ansari). Infinitesimal vs. Discrete Methods in Neural Networks Synthesis (A. Albrecht). GENETIC ALGORITHM AND GENETIC PROGRAMMING. Genetic Algorithms in Robotics (Y. Davidov). Efficient Multiprocessor Scheduling Based on Genetic Algorithms (E. Hou, et al.). Structure Evolution in Neural Systems (R. Lohmann). THE SOFTWARE OF CHAOS WITH APPLICATIONS. Dynamic vs. Genetic vs. Chaotic Programming: Pole Balancing (B. Maric ic). Parallel Scheduling of Random and of Chaotic Processes (C. Schelberg). Indexes.