We developed an original approach to cognition, based on the previously developed theory
of neural modeling fields and dynamic logic. This approach is based on the detailed …

Modeling of complex phenomena such as the mind presents tremendous computational
complexity challenges. The neural modeling fields theory (NMF) addresses these …

The paper describes neural dynamics of the knowledge instinct, determining adaptation and
evolution of consciousness. Evolution of consciousness is determined by complex dynamics …

First, it describes a new methodology, Probabilistic Rule Generator (PRG), of variable-
valued logic synthesis which can be applied effectively to noisy data. Then, an application of …

Theoretical research is predominately an inductive process; while applied research is
mainly a deductive process. Both inference processes are based on the cognitive process …

This monograph consists of new research results developed by the authors and their co-
authors, Zsolt Gera and Gábor Csiszár, and it focuses on a special class of continuous …

We consider a task-oriented approach to AGI, when any cognitive problem, perhaps
superior to human ability, has sense given a criterion of its solution. In the frame of this …

We describe computational foundations for Perceptual Symbol System (PSS). This requires
new mathematical methods of dynamic logic (DL), which have overcome limitations of …

The Boltzmann machine is a probabilistic neural network describing the associative
dependency of variables. It yields a probability distribution, which is a special case of the …

The classical McCulloch and Pitts neural unit is widely used today in artificial neural
networks (NNs) and essentially acts as a non-linear filter. Classical NN are only capable of …