Learning about an Absent Cause: Discounting and Augmentation of Positively and Independently Related Causes
Standard connectionist models of pattern completion like an auto–associator, typically fill in the activation of a missing feature with internal input from nodes that are connected to it. However, associative studies on competition between alternative causes, demonstrate that people do not always complete the activation of a missing feature, but rather actively encode it as missing whenever its presence was highly expected. Dickinson and Burke’s revaluation hypothesis  predicts that there is a novel cause, but that backward competition of a known cause depends on a consistent (positive) relation with the alternative cause. This hypothesis was confirmed in several experiments. These effects cannot be explained by standard auto–associative networks, but can be accounted for by a modified auto–associative network that is able to recognize absent information as missing and provides it with negative, rather than positive activation from related nodes.
KeywordsExternal Input Conditioned Inhibition Recurrent Network Causal Judgment Recurrent Model
Unable to display preview. Download preview PDF.
- 2.Busemeyer, J. R. (1991) Intuitive statistical estimation. In N. Anderson (Ed.) Contributions to Information integration theory, vol. 1: Cognition. Hillsdale, NJ: Erlbaum.Google Scholar
- 4.Dickinson, A. & Burke, J. (1996). Within-compound associations mediate the retrospective revaluation of causality judgments. Quarterly Journal of Experimental Psychology, 49 B, 60–80.Google Scholar
- 5.Graham, S. (1999). Retrospective revaluation and inhibitory associations: Does perceptual learning modulate our perceptions of the contingencies between events? Quarterly Journal of Experimental Psychology, 52 B, 159–185.Google Scholar
- 8.Matute, H. & Pineno, O. (1998). Stimulus competition in the absence of compound conditioning. Animal Learning and Behavior, 26. 3–14.Google Scholar
- 9.McClelland, J. M. & Rumelhart, D. E. (1988). Explorations in parallel distributed processing: A handbook of models, programs, and exercises. Cambridge, MA: Bradford.Google Scholar
- 10.Miller, R. R. & Matzel, L. D. (1988). The comparator hypothesis: A response rule for the expression of associations. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 22, pp. 51–92). San Diego, CA: Academic Press.Google Scholar
- 12.Rescoria, R. A. & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. In A. H. Black & W. F. Prokasy (Eds.) Classical conditioning II: Current research_and theory (pp. 64–98). New York: Appleton-Century-Crofts.Google Scholar
- 15.Van Overwalle, F. & Timmermans, B. (2000). Discounting and Augmentation in Attribution: The Role of the Relationship between Causes. Manuscript submitted for publication.Google Scholar
- 16.Wasserman, E. A. & Berglan, L. R. (1998). Backward blocking and recovery from overshadowing in human causal judgment: the role of within-compound associations. Quarterly Journal of Experimental Psychology, 5IB, 121–138.Google Scholar