Chapter 3. Problem solving

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Intelligence is nature’s answer to the logical and inference type of problems. Intelligence complies with the rules, and is perfectly fit for survival issues of a deterministic character. Within a certain set of premises, one evolves through reasoning from current state to a desired state of a given situation. Creativity, however, deals with problems that are so underdetermined and ill-defined, that reasoning falters, rules should be changed, and risky opportunities are explored. Creativity explores highly probabilistic and chaotic settings through disruptive association rather than reason. In the classical sense, problem solving is a goal-oriented activity and requires a set of strategies and procedures applied in a certain order. It involves cognitive processes to reach a preset goal. The overall goal that is to be achieved should be cut down to smaller sub-goals. Different strategies can be applied such as difference reduction, means-end analysis, or backward and forward reasoning. These strategies are all analytical and rule-based and can hardly deal with so-called ‘wicked problems,’ which are greatly underdetermined complexes of interacting problems that have no right or wrong answer. Such dilemmas or challenges need to be approached differently. They require intuition, empathy, and creativity, focusing less on specific goals. Which approach is chosen depends on whether a problem is well-defined or not. Because problems may have more answers, decisions should be made about the sort of solutions one wants. To do so, various contextual variables should be taken into account, for which many decision support-systems exist. Which system applies best to a problem depends on problem type (ill vs. well-defined), decision type (structured vs. unstructured), and underlying decision model (deterministic vs. probabilistic).


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