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.
