Abstract: A hybrid router for dynamical control systems is described. The mobile hybrid software router (MHSR) combines distinctive computational and mathematical techniques, including evolutionary computation (EC), probabilistic simulations (PS), machine learning and artificial neural networks (A-NNs), in order to solve unique problems encountered in an unknown environment in real time. Embodied in intelligent mobile software agents (IMSAs), the MHSR operates within a multi-agent system (MAS) to continually optimize system operation. The MHSR is applied to several major complex system categories. In one embodiment of the system, the MHSR is implemented in hardware, including continuously programmable field programmable gate arrays (CP-FPGAs), for perpetually reconfigurable evolvable hardware operation. Whether in application-specific or multi-functional mode, the MHSR is useful to groups of agents in intelligent systems for adaptation to uncertain environments in order to perform self-organization capabilities.

Abstract: A system, methods and apparatus are described involving the self-organizing dynamics of networks of distributed computers. The system is comprised of complex networks of databases. The system presents a novel database architecture called the distributed transformational spatio-temporal object relational (T-STOR) database management system (dbms). Data is continuously input, analyzed, organized, reorganized and used for specific commercial and industrial applications. The system uses intelligent mobile software agents in a multi-agent system in order to learn, anticipate, and adapt and to perform numerous functions, including search, analysis, collaboration, negotiation, decision making and structural transformation. The system links together numerous complex systems involving distributed networks to present a novel model for dynamic adaptive computing systems, which includes plasticity of collective behavior and self-organizing behavior in intelligent system structures.

Abstract: A system, methods and apparatus are described involving modular customized e-learning components. After an individual requests an e-learning process, databases are customized for him or her, thereby implementing just-in-time learning. The learner generates questions by using problem finding approaches and may use a personal learning agent. Collaboration between individuals is performed. In addition, a method is presented for conducting distributed classes both with and without (a teacher's) mediation. Part of the system involves a method featuring a dialectical learning process for problem solving. There is an automatic method to assess individual abilities.