Comparing associative, statistical, and inferential reasoning accounts of human contingency learning

摘要: For more than two decades, researchers have contrasted the relative merits of associative and statistical theories as accounts human contingency learning. This debate, still far from resolution, has led to further refinement models within each family theories. More recently, a third theoretical view joined debate: inferential reasoning account. The explanations these three differ critically in many aspects, such level analysis their emphasis on different steps information-processing sequence. Also, account important advantages (as well critical flaws) emphasizes experimental evidence that poses problems others. Some hybrid learning attempted reconcile certain features accounts, thereby benefiting some unique families accounts. A comparison will help us appreciate challenges research face over coming years.