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Case-based reasoning (CBR), broadly construed, is the process of solving new problems based on the solutions of similar past problems. [1] [2]In everyday life, an auto mechanic who fixes an engine by recalling another car that exhibited similar symptoms is using case-based reasoning.
The premises and the conclusion are propositions, i.e. true or false claims about what is the case. Together, they form an argument. Logical reasoning is norm-governed in the sense that it aims to formulate correct arguments that any rational person would find convincing. The main discipline studying logical reasoning is logic.
However, many reasoning systems implement imprecise and semi-formal approximations to recognised logic systems. These systems typically support a variety of procedural and semi-declarative techniques in order to model different reasoning strategies. They emphasise pragmatism over formality and may depend on custom extensions and attachments in ...
In propositional logic, disjunction elimination [1] [2] (sometimes named proof by cases, case analysis, or or elimination) is the valid argument form and rule of inference that allows one to eliminate a disjunctive statement from a logical proof.
Finally, a logic model of the intervention is developed. This model describes the various activities that will happen and the cascades of effects they are expected to cause toward the desired outcome. Evaluators thereafter use the logic model of the intervention to design a proper evaluation plan to assess implementation, impact and efficiency.
Le grand docteur sophiste, 1886 illustration of Gargantua by Albert Robida, expressing mockery of his casuist education. Casuistry (/ ˈ k æ zj u ɪ s t r i / KAZ-ew-iss-tree) is a process of reasoning that seeks to resolve moral problems by extracting or extending abstract rules from a particular case, and reapplying those rules to new instances. [1]
The procedural interpretation of logic programs, which uses backward reasoning to reduce goals to subgoals, is a special case of the use of a problem-solving strategy to control the use of a declarative, logical representation of knowledge to obtain the behaviour of an algorithm. More generally, different problem-solving strategies can be ...
Abductive logic programming (ALP) is a high-level knowledge-representation framework that can be used to solve problems declaratively, based on abductive reasoning. It extends normal logic programming by allowing some predicates to be incompletely defined, declared as abducible predicates. Problem solving is effected by deriving hypotheses on ...