It makes sense that the more information people share, the better they communicate. To evaluate the effect of knowledge overlap on the effectiveness of communication, participants played a communication game where the “director” identified objects to the “addressee”. Pairs either shared information about most objects' names (high overlap), or about the minority of objects' names (low overlap). We found that high-overlap directors tended to use more names than low overlap directors. High overlap directors also used more names with objects whose (...) names only they knew, thereby confusing their addressees more often than low-overlap directors. We conclude that while sharing more knowledge can be beneficial to communication overall, it can cause communication to be locally ineffective. Sharing more information reduces communication effectiveness precisely when there is an opportunity to inform—when people communicate information only they themselves know. (shrink)

The notion of common ground is important for the production of referring expressions: In order for a referring expression to be felicitous, it has to be based on shared information. But determining what information is shared and what information is privileged may require gathering information from multiple sources, and constantly coordinating and updating them, which might be computationally too intensive to affect the earliest moments of production. Previous work has found that speakers produce overinformative referring expressions, which include privileged names, (...) violating Grice’s Maxims, and concluded that this is because they do not mark the distinction between shared and privileged information. We demonstrate that speakers are in fact quite effective in marking this distinction in the form of their utterances. Nonetheless, under certain circumstances, speakers choose to overspecify privileged names. (shrink)

This paper presents two cognitive models that simulate the production of referring expressions in the iMAP task—a task-oriented dialog. One general model is based on Dale and Reiter’s (1995)incremental algorithm, and the other is a simple template model that has a higher correlation with the data but is specifically geared toward the properties of the iMAP task. The property of the iMAP task environment that is modeled here is that the color feature is unreliable for identifying referents while other features (...) are reliable. The low computational cost of the incremental algorithm for generating referring expressions makes it an interesting starting point for a cognitive model. However, its explanatory power is limited, because it generates uniquely distinguishing referring expressions and because it considers features for inclusion in the referring expression in a fixed order. The first model extends the original incremental algorithm by an ability to adapt to feedback of whether a referring expression was used successfully, but it seems to overpredict the frequency with which distinguishing expressions are made and underpredict the frequency of overspecified referring expressions. The second model produces features for referring expressions purely based on its current estimate of a feature’s utility. Both models predict the observed human behavior of decreasing use of color terms and increasing use of useful feature terms. (shrink)

Is language understanding a special case of social cognition? To help evaluate this view, we can formalize it as the rational speech-act theory: Listeners assume that speakers choose their utterances approximately optimally, and listeners interpret an utterance by using Bayesian inference to “invert” this model of the speaker. We apply this framework to model scalar implicature (“some” implies “not all,” and “N” implies “not more than N”). This model predicts an interaction between the speaker's knowledge state and the listener's interpretation. (...) We test these predictions in two experiments and find good fit between model predictions and human judgments. (shrink)