Abstract: This paper summaries basic principles and concepts of
intelligent controls, implemented in humanoid robotics as well as
recent algorithms being devised for advanced control of humanoid
robots. Secondly, this paper presents a new approach neuro-fuzzy
system. We have included some simulating results from our
computational intelligence technique that will be applied to our
humanoid robot. Subsequently, we determine a relationship between
joint trajectories and located forces on robot-s foot through a
proposed neuro-fuzzy technique.
Abstract: This paper shows possibility of extraction Social,
Group and Individual Mind from Multiple Agents Rule Bases. Types
those Rule bases are selected as two fuzzy systems, namely
Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are
describing (modeling) agent behavior. Modifying of agent behavior
in the time varying environment will be provided by learning fuzzyneural
networks and optimization of their parameters with using
genetic algorithms in development system FUZNET. Finally,
extraction Social, Group and Individual Mind from Multiple Agents
Rule Bases are provided by Cognitive analysis and Matching
criterion.