Equilibria of the Rescorla-Wagner Model 1 Equilibria of the
The Rescorla-Wagner model has been a leading theory of animal causal induction for nearly thirty years, and human causal induction for the past fifteen. Recent theories (especially Cheng, 1997) have provided alternative explanations of how people draw causal conclusions from covariational data. However, theoretical attempts to compare the Rescorla-Wagner model with more recent models have been hampered by the fact that the Rescorla-Wagner model is an algorithmic theory, while the more recent theories are all computational. This paper provides a detailed derivation of the long-run behavior of the Rescorla-Wagner model under a wide range of parameters and experimental setups, so that the model can be compared with computational theories. It also shows that the model agrees with competing theories on a wider range of cases than had previously been thought. The paper concludes by showing how recent suggested modifications of the Rescorla-Wagner model impact the long-run behavior of the model.