A novel approach to decision engineering, with a verified framework
for modeling human reasoning Soft Computing Evaluation Logic
provides an in-depth examination of evaluation decision problems
and presents comprehensive guidance toward the use of the Logic
Scoring of Preference (LSP) method in modeling complex decision
criteria. Fully aligned with current developments in computational
intelligence, the discussion covers the design and use of LSP
criteria for evaluation and comparison in diverse areas, such as
search engines, medical conditions, real estate, space management,
habitat mitigation projects in ecology, and land use and
residential development suitability maps, with versatile transfer
to other similar decision-modeling contexts. Human decision making
is rife with fuzziness, imprecision, uncertainty, and
half-truths--yet humans make evaluation decisions every day. In
this book, such decision processes are observed, analyzed, and
modeled. The result is graded logic, a soft computing mathematical
infrastructure that provides both formal logic and semantic
generalizations of classical Boolean logic. Graded logic is used
for logic aggregation in the context of evaluation models
consistent with observable properties of human reasoning. The LSP
method, based on graded logic and logic aggregation, is a vital
component of an industrial-strength decision engineering framework.
Thus, the book: Provides detailed theoretical background for graded
logic Provides a theory of logic aggregators Explains the LSP
method for designing complex evaluation criteria and their use
Shows techniques for evaluation, comparison, and selection of
complex systems, as well as the cost/suitability analysis,
optimization, sensitivity analysis, tradeoff analysis, and
missingness-tolerant aggregation Includes a survey of available LSP
software tools, including ISEE, ANSY and LSP.NT. With quantitative
modeling of human reasoning, novel approaches to modeling decision
criteria, and a verified decision engineering framework applicable
to a broad array of applications, this book is an invaluable
resource for graduate students, researchers, and practitioners
working within the decision engineering realm.
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