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Chaining is a technique used in applied behavior analysis to teach complex tasks by breaking them down into discrete responses or individual behaviors that are part of a task analysis. [1] With a backward chaining procedure the learning can happen in two ways. In one approach the adult can complete all the steps for the learner and give the ...
Backward chaining (or backward reasoning) is an inference method described colloquially as working backward from the goal. It is used in automated theorem provers , inference engines , proof assistants , and other artificial intelligence applications.
The biggest benefit of using a backward chain is that the learner receives the terminal reinforcer (the outcome of the behavior chain) naturally. Backward chaining is the preferred method when teaching skills to individuals with severe delays because they complete the last step and see the direct outcome of the chain immediately rather than ...
Backward induction is the process of determining a sequence of optimal choices by reasoning from the endpoint of a problem or situation back to its beginning using individual events or actions. [1] Backward induction involves examining the final point in a series of decisions and identifying the optimal process or action required to arrive at ...
Back-chaining is a technique used in teaching oral language skills, especially with polysyllabic or difficult words and phrases. [1] The teacher pronounces the last syllable, the student repeats, and then the teacher continues, working backwards from the end of the word to the beginning.
Cwm, a forward-chaining reasoner used for querying, checking, transforming and filtering information. Its core language is RDF, extended to include rules, and it uses RDF/XML or N3 serializations as required. Drools, a forward-chaining inference-based rules engine which uses an enhanced implementation of the Rete algorithm.
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Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved. [1]