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Classical conditioning occurs when a conditioned stimulus (CS) is paired with an unconditioned stimulus (US). Usually, the conditioned stimulus is a neutral stimulus (e.g., the sound of a tuning fork), the unconditioned stimulus is biologically potent (e.g., the taste of food) and the unconditioned response (UR) to the unconditioned stimulus is an unlearned reflex response (e.g., salivation).
In backward blocking, the subject is exposed to the compound stimulus (CS1 and CS2 together) first, and only later to CS1 alone. In some human and animal studies, subjects show a reduction in the association between CS2 and the US, though the effect is often weaker than the standard blocking effect, and vanishes under some conditions.
The US preceded the CS, rather than the other way around. In the backward conditioning control procedure popular with Pavlov, his dogs did not salivate to the presentation of the CS, in contrast to those that received forward conditioning. However, the dogs did learn something - the presentation of the metronome predicted the absence of the food.
An example of second-order conditioning. In classical conditioning, second-order conditioning or higher-order conditioning is a form of learning in which a stimulus is first made meaningful or consequential for an organism through an initial step of learning, and then that stimulus is used as a basis for learning about some new stimulus.
Backward chaining is the procedure that is typically used for people with limited abilities. This process uses prompting and fading techniques to teach the last step first. The biggest benefit of using a backward chain is that the learner receives the terminal reinforcer (the outcome of the behavior chain) naturally.
Computing the square root of 2 (which is roughly 1.41421) is a well-posed problem.Many algorithms solve this problem by starting with an initial approximation x 0 to , for instance x 0 = 1.4, and then computing improved guesses x 1, x 2, etc.
Condition numbers can also be defined for nonlinear functions, and can be computed using calculus.The condition number varies with the point; in some cases one can use the maximum (or supremum) condition number over the domain of the function or domain of the question as an overall condition number, while in other cases the condition number at a particular point is of more interest.
[7] [8] [9] In practice, there are two types (modes) of algorithmic differentiation: a forward-type and a reversed-type. [ 3 ] [ 4 ] Presently, the two types are highly correlated and complementary and both have a wide variety of applications in, e.g., non-linear optimization , sensitivity analysis , robotics , machine learning , computer ...