decision problem

(redirected from Decision problems)

decision problem

(theory)
A problem with a yes/no answer. Determining whether some potential solution to a question is actually a solution or not. E.g. "Is 43669" a prime number?". This is in contrast to a "search problem" which must find a solution from scratch, e.g. "What is the millionth prime number?".

See decidability.
References in periodicals archive ?
The conventional crisp techniques have been not much effective for solving decision problems because of imprecise or fuzziness nature of the linguistic assessments.
But today computers have replaced paper and pencils, and sophisticated software can explore, simulate and identify optimal or near-optimal solutions to complex decision problems using far more realistic assumptions.
As a structured approach to those decision problems around cognitive systems, we see a pattern emerging in our research.
Pal, Fuzzy Preference Ordering of Interval Numbers in Decision Problems.
Second, formal analysis of decision problems in UI design allows combating a broader range of design tasks with efficient and appropriate optimization methods.
In our daily lives or professional settings, there are many decision problems involving multiple criteria, which may be conflicting and incommensurable.
3 Description of data structure decision problems under consideration
Of these characteristics, there is a precedent for studying resilience in relation to decision problems.
This method can be applied for any decision problems considering any number of alternatives.
Thus, choosing the right construction project partners has been one of the most important decision problems that require delicate care.
Other contributions review penetration testing tools, rules for designing security applications, data stream anonymization schemes, transform domain techniques for image steganography, and decision problems for guiding the construction of digital forensic tools.
Sequential decision problems that exhibit adaptive submodularity in their structure can be solved efficiently using greedy policies with provable near-optimality.