By Peter A. Flach, Antonis C. Kakas (auth.), Peter A. Flach, Antonis C. Kakas (eds.)
From the very starting in their research of human reasoning, philosophers have pointed out other kinds of reasoning, in addition to deduction, which we now name abduction and induction. Deduction is now relatively good understood, yet abduction and induction have eluded the same point of knowing. The papers gathered right here handle the connection among abduction and induction and their attainable integration. The process is typically philosophical, occasionally that of natural good judgment, and a few papers undertake the extra task-oriented process of AI.
The booklet will command the eye of philosophers, logicians, AI researchers and machine scientists in general.
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Extra info for Abduction and Induction: Essays on their Relation and Integration
Too much of the wrong kind of creativity is a drain on intelligence, and so is not smart. Generation of hypotheses, without critical control, is not smart. Generation of hypotheses, as a pattern of inference, in and of itself, is not smart. Generation of plausible explanatory hypotheses, relevant to the current explanatory problem, is smart. Yet pre-screening hypotheses to remove those that are implausible or irrelevant mixes critical evaluation into the hypothesis-generation process, and so breaks the separation between the process of hypotheses generation and the process of critical evaluation.
3: All objects in the sample satisfy P(x); therefore, all objects in the population satisfy P(x) . As with Peirce's syllogisms, the problem here is that P(x) is already assumed to be given, while in AI a major problem is to generate such hypotheses. g. the truth-minimal model). This specification can be seen as sample-to-population inference. For example, in Peirce's bean example (p. 5), B is 'these beans are from this bag' (instance knowledge), 0 is 'these beans are white' (observation), and H- 'all the beans from this bag are white' - is satisfied by the model containing 'these beans' as the only beans in the universe.
KAKAS knowledge generated. 2, on one side of this cycle we have induction, its output feeding into the theory T for later use by abduction, as shown in the other half of the cycle, where the abductive output in tum feeds into the observational data 0 for later use by induction, and so on. Inducing abductive theories. Another way in which induction can feed into abduction is through the generation of confirmatory (or descriptive) inductive hypotheses that could act as integrity constraints for the new theory.