In an earlier study, we modeled subjects' beliefs in textually embedded propositions with E C H O , a computational system for simulating explanatory evaluations (Schank & Ranney, 1991). W e both presumed and found that subjects' representations of the texts were not completely captured by the (a priori) representations generated and encoded into E C H O ; extraneous knowledge likely contributed to subjects' biases toward certain hypotheses. This study builds on previous work via two questions: First, h o w well can E C H O predict subjects' belief evaluations when a priori representations are not used? To assess this, w e asked subjects to predict (and explain, with alternatives) an endpoint pendular-release trajectory, while collecting believability ratings for their on-line beliefs; subjects' protocols were then "blindly" encoded and simulated with E C H O , and their ratings were compared to ECHO'S resulting activations. Second, how similar are different coders' encodings of the same reasoning episode? T o assess intercoder agreement, w e examined the fit between ECHO'S activations for coders' encodings of the same protocols. W e found that intercoder correlations were acceptable, and E C H O predicted subjects' ratings well—almost as well as those from the more diminutive, constrained situations modeled by Schank and Ranney (1991).

The problem of evaluating explanatory hypotheses is to choose the hypothesis or theory that best accounts for, or explains, the given evidence. Thagard (e.g.. 1989) and Ranney (in press; Ranney & Thagard, 1988) describe a theory of explanatory coherence intended to account for a variety of explanatory evaluations; this theory has been implemented in a coimectionist computer model, ECHO. In this study, we examine three questions regarding the relationship between human explanatory reasoning and echo's explanatory evaluations: Does E C H O predict subjects' evaluations of interrelated propositions? Are local temporal order differences (not explicitly modeled by ECHO) important to the subjects? Does E C H O predict subjects' inflectional reasoning? W e found that subjects often entertain competing hypodieses as nonexclusive and presume an implied backing for certain (superordinate) hypotheses. These tendencies were modeled in E C H O by assigning a fraction of data priority (usually reserved for evidence) to the superordinate hypotheses. In simi, the E C HO model helps to interpret subjects' reasoning patterns, and shows continued potential for simulating explanatory coherence processes.

The Theory of Explanatory Coherence, or TEC, (Ranney & Thagard, 1988; Thagard. 1989, 1992) and ECHO, a connectionist implementation of TEC, attempt to model human reasoning about evidence and hypotheses. The ECH O model is based on the simultaneous satisfaction of multiple constraints. This yields predicted activations ("believabilities") for propositions, which are based on the propositions' evidential status, their explanatory relationships, and their contradictory relationships. While ECH O has been demonstrated to usefully model human reasoning, it does not model processing limitations on the maintenance of coherence. WanderECHO is a variation on the ECH O model that attempts to simulate attentional and memorial limitations with a stochastic updating algorithm that is based on a traveling focus of attention. Several variants of the WanderECHO simulation were applied to Schank and Ranney's (1991) data, and were found to generally simulate subjects' mean believability ratings better than standard ECHO.