Editing Classical conditioning (section)

====Equation====
<math display="block">\Delta V=\alpha\beta (\lambda - \Sigma V)</math>

This is the Rescorla-Wagner equation. It specifies the amount of learning that will occur on a single pairing of a conditioning stimulus (CS) with an unconditioned stimulus (US). The above equation is solved repeatedly to predict the course of learning over many such trials.

In this model, the degree of learning is measured by how well the CS predicts the US, which is given by the "associative strength" of the CS. In the equation, V represents the current associative strength of the CS, and ∆V is the change in this strength that happens on a given trial. ΣV is the sum of the strengths of all stimuli present in the situation. λ is the maximum associative strength that a given US will support; its value is usually set to 1 on trials when the US is present, and 0 when the US is absent. α and β are constants related to the salience of the CS and the speed of learning for a given US. How the equation predicts various experimental results is explained in following sections. For further details, see the main article on the model.<ref name="Chance_2008" />{{rp|85–89}}