Causal Induction 1 Running head : Continuous Causal Inference Causal Induction from Continuous Event Streams

Three experiments investigated the impact of delay on human causal learning. We present a new paradigm based on the presentation of continuous event streams, and use it to test two hypotheses drawn from associative learning theories of causal inference. Unlike free-operant procedures traditionally used to study temporal aspects of causal learning (Shanks, Pearson, & Dickinson, 1989; Shanks & Dickinson, 1987; Buehner & May, 2002, 2003, 2004), the procedure employed here allows full control over all aspects of stimulus delivery while at the same time overcoming the ecologically invalid notion of discrete learning trials. Results show that delays generally impair causal learning, but prior knowledge and experience mediate this detrimental effect. In accordance with associative learning theory, pre-exposure to an unreinforced background context facilitates the discovery of delayed causal relationships. However, contrary to associative learning theory, increasing the amount of experience with a delayed causal relationship does not improve discovery. Implications for associative learning and causal model theories are discussed.