Computation theory is a discipline that uses mathematical concepts and
tools to expose the nature of "computation" and to explain a broad range
of computational phenomena: Why is it harder to perform some
computations than others? Are the differences in difficulty that we
observe inherent, or are they artifacts of the way we try to perform the
computations? How does one reason about such questions?
This unique textbook strives to endow students with conceptual and
manipulative tools necessary to make computation theory part of their
professional lives. The work achieves this goal by means of three
stratagems that set its approach apart from most other texts on the
subject.
For starters, it develops the necessary mathematical concepts and tools
from the concepts' simplest instances, thereby helping students gain
operational control over the required mathematics. Secondly, it
organizes development of theory around four "pillars," enabling students
to see computational topics that have the same intellectual origins in
physical proximity to one another. Finally, the text illustrates the
"big ideas" that computation theory is built upon with applications of
these ideas within "practical" domains in mathematics, computer science,
computer engineering, and even further afield.
Suitable for advanced undergraduate students and beginning graduates,
this textbook augments the "classical" models that traditionally support
courses on computation theory with novel models inspired by "real,
modern" computational topics, such as crowd-sourced computing, mobile
computing, robotic path planning, and volunteer computing.
Arnold L. Rosenberg is Distinguished Univ. Professor Emeritus at
University of Massachusetts, Amherst, USA. Lenwood S. Heath is
Professor at Virgina Tech, Blacksburg, USA.
