This book was born from the belief that, in an era of narrowly
specialized experts, looking beyond the arbitrary borders on one's own
field offered the only chance for intellectual survival. The spectacular
growth of economics in the past forty years or so has been accompanied
by the rapid fragmentation process that seems to characterize the making
of any science. If we chose to view this as a symptom of scientific
maturity, we would be tempted to welcome this process. But, as
economists, we should think of its opportunity cost. In one sense this
work attempts to assess the price we have chosen to pay - consciously or
not - to win recognition of our scientific status from other
disciplines. If, after going through this book, the reader comes out
with the feeling that this shadow price is not all shadow after all, we
will have achieved one of our goals! Both the merits and defects of this
book stem from the fact that we tried to pursue a different approach in
the study of economics. This line of thought originates in the area of
pattern recognition and machine learn- ing. For the past two decades, a
number of applied mathematicans, logicians, and engineers have
systematically tried to mimic human intelli- gence in one of its most
important functions viz. that of identifying and recognizing patterns in
an a priori unorganized and confusing environment.