(19th-August-2020)
• Abduction is a form of reasoning where assumptions are made to explain observations. For example, if an agent were to observe that some light was not working, it can hypothesize what is happening in the world to explain why the light was not working. An intelligent tutoring system could try to explain why a student gives some answer in terms of what the student understands and does not understand.
• The term abduction was coined by Peirce (1839-1914) to differentiate this type of reasoning from deduction, which involves determining what logically follows from a set of axioms, and induction, which involves inferring general relationships from examples.
• In abduction, an agent hypothesizes what may be true about an observed case. An agent determines what implies its observations - what could be true to make the observations true. Observations are trivially implied by contradictions (as a contradiction logically implies everything), so we want to exclude contradictions from our explanation of the observations.
• To formalize abduction, we use the language of Horn clauses and assumables (the same input that was used for proving from contradictions). The system is given
• a knowledge base, KB, which is a set of of Horn clauses, and
• a set A of atoms, called the assumables; the assumables are the building blocks of hypotheses.
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