Abduction is a syllogism with a certain major premise but a probable minor premise. It involves inference using the available best explanation. The hypotheses generated explanations, conclusions and observations. Broadly speaking, the aim of abduction is to find the causes or explanations of facts or observed phenomenon. In deduction, premises cannot guarantee conclusion unlike in induction where premises guarantee conclusion. In induction, one can believe that conclusion is based on the premise but the truth of the conclusion is not guaranteed. Abduction is a logical fallacy that affirms the consequent. It serves as a hypothesis to explain our observation. While there are infinite explanations to the observed phenomena, abduction enables one to form a few or one explanation. Thus, abduction helps to disregard certain possibilities. Consequently, we are able to orient ourselves to our environment better.
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Current essay will provide a classification of abduction. The paper will be premised upon Artificial Intelligence (AI) and philosophy. Towards this end, it will provide interesting philosophical debates and arguments. Moreover, to understand abduction, a historical background of this concept will be provided with attribution to certain philosophers’ works. The essay will provide a detailed examination coupled with personal ideas and opinions regarding Artificial Intelligence (AI). It will classify abduction as part of Artificial Intelligence (AI) and logic. Lastly, the essay will provide recent arguments regarding this issue.
Originally, Aristotle introduced abduction but Sanders Pierce introduced it to the modern logic. Pierce called such inference retroduction, presumption, abduction, and hypothesis over many years. He developed abduction to an explicit inference theory. He argued that the traditional inference modes, such as deduction and induction, need a third inference mode, that is, abduction. He claimed that abduction was qualitatively dissimilar from deduction and induction. Abduction infers cases from a result and a rule. Like induction, the abduction inference is not probable, and not certain. Pierce considers abduction as a process that facilitates gaining of knowledge, which is predicated on observed facts. Abduction and induction collapse in the hypothesis, a single overarching concept. Indeed, the abduction stage of hypothesis formation is conceptualized as induction in the scientific methods pioneered by Bacon and Galileo. In the 20th century, the hypothetic-deductive model as exemplified by Popper reinforced the collapse of induction and abduction into a hypothesis. Karl Popper posits that a hypothesis is just an ‘intelligent guess.’ The result of this process is hypothesis formation.
Before 1900, Sanders Pierce considered abduction as the utilization of rules in order to explain observations. It is the common use of abduction in artificial intelligence and social sciences. The logic of abduction is pragmatism since it guesses an outside or newfangled idea. In 1867, Pierce contended that hypothetical inferences deal with many characters. In 1878, he argued that there is no need to have multiple predicates or characters for hypothetical inference, but was still helpful. Today, abduction is regarded as induction from extension and characters of known rules in order to cover unsolved circumstances. In 1902, Pierce argued that syllogistical forms as well as doctrine of comprehension and extension are less fundamental. Hypotheses are framed in premises not asserted. Pierce posited that abduction is non-deductive inference since it involves the formation of explanatory hypotheses. In fact, abduction
Induction and deduction are involved in late stages of assessment of theories. Deduction assists in the derivation of testable consequences. Abduction enables us to conceive explanatory hypothesis. While induction enables us to give a verdict on a hypothesis. According to Pierce, abduction has schematic characterization associated with science. To Frankfurt, abduction involves adopting hypotheses and not necessarily inventing hypotheses. However, abduction can still be considered as integral in the discovery context. The presence of many hypotheses accounting for an assortment of facts does not suffice hypothesis adoption. Thus, abduction is inference to best explanation that evolves from data description to a hypothesis, which accounts or explains the data. Abduction culminates to interpretive inference or theory formation. The logician and philosopher Sanders Peirce argues that in daily life and science, there exists a distinct reasoning pattern, which involves the formation of explanatory hypotheses and acceptance called abduction.
McDermott and Charniak (1985), in their Artificial Intelligence (AI) characterize abduction variedly as turned backward modus ponens. They argue that story understanding, comprehension natural language, and medical diagnosis is abduction process. Abductions exist in unselfconscious reasoning, interpretations, and perception of life. Sometimes abductions can be deliberate like when a mechanic, detective, scientist, and physician form explicit hypotheses and evaluate them to get the unsurpassed explanation. Abductions can be perpetual sometimes after separation of background from foreground planes. Abductive reasoning can be considered commonsensical and ordinary. For instance, Schurz (2013), posits that people can infer from people’s behavior to facts about their mental state, they are inferring that this fact provides an explanation to their behavior.
In science, abductions are small and large-scale scientific reasoning. Newton’s gravitation theory persuasiveness was bolstered by its capacity to explain planets motion and tides’ occurrence. Scientists infer the subsistence of subatomic and atoms particles. Historical past knowledge is predicated on abductions. For instance, innumerable documents and files refer to Napoleon Bonaparte. Monuments and documents provide explanation of his existence. Sometimes, abduction can refer to hypothesis-generation phase. However, abduction can be considered as the entire hypothesis generation process, criticism, and explanatory hypotheses acceptance. In Artificial Intelligence (AI), diagnosis is an abduction problem. Diagnosis produces explanation that accounts for the device’s symptoms. The responsibility of the diagnostic reasoned is thus to generate the symptoms’ best explanation. Malfunction hypotheses are the most appropriate explanatory hypotheses for diagnosis. Thus, diagnostic task aims at finding an assortment of malfunctions, which explains symptoms best.