The field of artificial intelligence (AI), formally founded in 1956,
attempts to understand, model and design intelligent systems.
Since the beginning of AI, two alternative
approaches were pursued to model intelligence:
on the one hand, there was
the symbolic approach which was a mathematically oriented way of
abstractly describing processes leading to
intelligent behaviour.
On the other hand, there was
a rather physiologically oriented approach, which favoured
the modelling of brain functions in order to reverse-engineer intelligence.
Between the late 1960s and
the mid-1980s, virtually all research in the field of AI and
cognitive science was conducted in the symbolic paradigm.
This was due to the
highly influental analysis of the capabilities and limitations of the perceptron
by [Minsky and Papert, 1969]. The perceptron was
a very popular neural model at that time.
In the mid-1980s a renaissance of neural networks
took place under the new title of connectionism,
challenging the dominant symbolic paradigm of AI.
The `brain-oriented' connectionist paradigm
claims
that research in the traditional symbolic paradigm cannot be successful
since symbols are insufficient to model crucial aspects
of cognition and intelligence.
Since then a debate between
the advocates of both paradigms is taking place,
which frequently tends to become polemic
in many writings on the virtues and
vices of either the symbolic or the connectionist paradigm.
Advocates on both sides have often neither appreciated nor really
addressed each others arguments or concerns.
Besides this somewhat frustrating state of the debate,
the main motivation for writing this book
was the methodological analysis
of both paradigms, which is presented in part III
of this book and which I feel has been long overdue.
In part III,
I set out to develop criteria which any successful method
for building AI systems and any successful theory
for understanding cognition has to fulfill.
The main arguments put forward by the
advocates on both sides fail to address the methodologically important
and ultimately decisive question for or against a paradigm:
How feasible is the development of an AI system or the
understanding of a theory of cognition?
The significance of this question is:
it is not only the nature of an intelligent system
or the phenomenon of cognition itself which
plays the crucial role, but also the human subject who
is to perform the design or who wants to understand
a theory of cognition.
The arguments for or against one of the paradigms have, by and large,
completely forgotten the role of the human subject.
The specific capabilities and limitations of the human subject
to understand a theory or a number of design steps needs to be an instrumental
criterion in deciding which of the paradigms is more appropriate.
Furthermore, the human subject's capabilities
and limitations have to provide the guideline for the development
of more suitable frameworks for AI and cognitive science.
Hence, the major theme of this book
are methodological considerations regarding the form and purpose of
a theory, which could and should be the outcome of our
scientific endeavours in AI and cognitive science.
This book is written for researchers, students, and technically skilled
observers of the
rapidly evolving fields of AI and
cognitive science alike.
While the third part is putting forward my methodological
criticism, part I and II
While the third part is putting forward my methodological
criticism, part I and II
provide the fundamental ideas and basic techniques of the symbolic
and connectionist paradigm respectively.
The first two parts are mainly written for
those readers, which are new to the field, or are
only familiar with one of the paradigms, to allow an easy grasp of the
essential ideas of both paradigms.
Both parts present the kernel of each paradigm without
attempting to cover the details of latest developments,
as those do not affect the fundamental ideas.
The methodological analysis of both paradigms with respect to their
suitability for building AI systems and for understanding cognition
is presented in part III.
Available from Springer-Verlag worldwide.
Here are links to
Springer-Verlag Germany,
USA,
Hong Kong.
ISBN 981-3083-97-2