Abstract
The von Neumann architecture was first expressed in 1945
and has largely dominated in many variants and refinements computer
science for more than half a century. Alternative architectures always
occupied a marginal place only, despite a growing need for new
concepts and paradigms in computer science.
Biologically-inspired engineering applies biological concepts to the
design of novel computing machines and algorithms. This can lead to
the creation of new machines, endowed with properties usually
associated with the living world: adaptation, evolution, growth and
development, fault-tolerance, self-replication or cloning,
reproduction, etc. Most of these approaches are based on well
established theories such as artificial neural networks, evolutionary
algorithms, and cellular automata.
The work presented in this thesis takes an alternative path and
proposes concepts for novel and unconventional biologically-inspired
machines. The approach is mainly motivated by the insight that
tomorrow's computational substrates and environments might be very
different from what we know today. Some of tomorrow's computers might
be embedded in the paint that covers your desk or printed on a sheet
of paper by means of a special ink. Most of such pervasive computing
concepts have some common elements: (1) the computer's basic elements
are very simple, identical, and available in a huge number, (2) the
interactions between the elements are purely local, (3) the elements
as well as the interconnections are unreliable, and (4) there is no
global control mechanism available.
This thesis is mainly based on the unification of the following three
domains of research: (1) amorphous computing, (2) membrane systems,
and (3) blending.
An amorphous computer is a massive parallel machine made up of myriads
of simple, unreliable, and identical elements, distributed randomly on
a surface and interconnected locally by unreliable
connections. Membrane systems are theoretical models inspired by
biochemistry-based on regions bounded by membranes. The hierarchical
membrane structures contain artificial chemistries, consisting in
objects and reactions, which allow to do computations. Blending is a
framework of cognitive science which tries to explain how we deal with
mental concepts and how creative thinking emerges.
First, an introduction of traditional bio-inspired machines and
hardware is provided. This part also includes the presentation of a
first implementation of a membrane system on reconfigurable hardware
and a description of the cellular automata machine entitled BioWall,
with its applications. Random boolean networks as well as several
theoretical considerations and practical results are then used to
introduce irregular computational structures.
The C-Blending approach represents an novel computational blending
method intended for membrane systems and artificial chemistries. In
order to implement membrane systems on amorphous computers, the
Circuit Amorphous Computer as well as special membrane systems,
termed aP and aB membrane systems, are proposed. The ultimate
concept proposed and studied consists in a unification of membrane
systems, amorphous computers, and computational C-Blending.
The unification of the three concepts results in several interesting
properties. The cellular structures allow to create dynamical
hierarchies and growing systems whereas the artificial chemistries
represent an ideal mean to compute on the potentially imperfect and
irregular hardware of an amorphous computer. Finally, the
computational blending proposed describes an inventive method to
create, organize, and adapt membrane systems.
The characteristics and limits of the concepts proposed are analyzed
and validated using various examples and toy applications. The thesis
concludes with the definition of the Circuit Amorphous Computer
and the Amorphon architecture, which might constitute the
minimal element of tomorrow's computing machines.