Objective: Every TOE must encompass two extremes, the fundamental laws of physics and the complex phenomena of a living system. Starting from Conway's __Game of Life__, the **automata networks paradigm** has constructed a model which could give an autonomous behavior to some artificial living systems, with a level of complexity close to the natural life. However, the local transition function (f) which governs evolution of the automata networks has no any connection with the laws of physics which are, nonetheless, the confining laws for natural life. Dr. Tienzen Gong's __Prequark Theory__ finally links the quark theory of physics to Conway's __Game of Life__. This research program plans to construct a model for biological life system by using the automata networks approach while the dynamics of the system is governed by the laws of physics.

One, Starting points:

- Automata Networks Theory
- Quark Theory
- Prequark Theory

Two, scope of the project:

- Laws of self-organization
- Order-disorder transition
- Collective behaviors
- Chaotic behaviors
- Artificial life
- Quantum computation
- Quark theory
- Prequark theory

Three, expected results:

- A generalization of Conway's
__Game of Life__ - A connection between
**biological (artificial) living system**and**automata networks** - A connection between
**automata networks**and**Prequark Theory**

Four, epistemology of automata networks --- the validity of any result from automata networks approach is based on two steps:

- The foundation, V(0) -- the validity of the foundation of automata networks approach is based on mathematical models and demonstrated by Von Bertalanffy, Corning, Prigogine and others.
- The evolution --- the first generation of an automata networks, A(1) is validated with V(0); then, V(0) + A(1) becomes V(1). The validity of subsequent generations, A(n), are obtained with the interplay of two processes.
- Internal evolution -- all subsequent generations, A(n), are evolved with a set fixed internal rules and are validated with V(n-1), and V(n-1) together with A(n) becomes V(n).
- external adaptation -- any result of subsequent generations, A(n), is checked with external facts (knowledge), such as, laws of physics, mathematics, biology, etc.,especially, checked with a new epistemology.

Five, this work will be published in:

__International Journal of Modern Physics B__- or
__Modern Physics Letters B__

- Automata networks: are modeled by
**cells**and**interaction rules**, are indefinitely extended networks of trivially small, identical, uniformly interconnected, and synchronously clocked digital computers. From the mathematical point of view,**automata networks**are given by a tuple (C, N, Q, f), where C is the cellular space, N is the neighborhood, Q is the set of cell states and f is the local transition function which associates a new state to each cell, depending on the cell state itself and the each state configuration in the neighborhood. The dynamics of the automata networks is given by the synchronous application of the local function, f, to all the cells in the cellular space. - Automata networks paradigm: is developed on basis of two important principles:
- The local activity
- The synchronous parallel computation

Dr. Andrecut's papers published on the WWW (Internet)

- Logistic map, an ideal random number generator
- On the ergodic behavior of a thermostated harmonic oscillator
- Parallel computation in the game of life (and other cellular automata)
- Biomorphs, computing biological shapes