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This paper explores the uncertainty aspects of human abductive reasoning. Echo, a model of abduction based on the Theory of Explanatory Coherence (Thagard, 1992a), captures many aspects of human abductive reasoning, but fails to sufficiently manage the uncertainty in abduction. In particular, Echo does not handle belief acquisition and dynamic belief revision, two essential components of human abductive reasoning. We propose a modified Echo model (UEcho), in which we add a learning mechanism for belief acquisition and a dynamic processing mechanism for belief revision. To evaluate the model, we report an empirical study in which base rate learning serves as a testbed for belief acquisition and the order effect serves as a testbed for belief revision.

This study examines the effects of representational forms on the acquisition and transfer of problem solving strategies. Three isomorphic representations of the Tic-Tac-Toe are used as the experimental tasks. The experiment shows that different representations of a common structure lead to the discovery of different forms of a common strategy with varying degrees of generality. With a better representation, subjects not only learn faster but also acquire more general forms of the strategy. The transfer across different representations can be either positive or negative, and it is based on strategies, not on problem structures.

This paper addresses three hypotheses concerning the procedural/declarative distinction: 1) Procedural and declarative knowledge speed-up as separate, but parallel, power curves; 2) Procedural knowledge operates in one direction only—from condition to action—hereas declarative knowledge can be cued by any of its elements; and 3) Declarative knowledge is active—it can result in behavior independent of procedural knowledge. The paper presents a single Act-R model that closely fits the data of two learning and transfer experiments conducted by Rabinowitz and Goldberg (1995). The model provides a good fit to the data, further validating Act-R as a model of the human cognitive architecture. In addition, the model shows that the two experiments cannot be used to argue that declarative knowledge can be retrieved without any intervening procedural knowledge.

Dissociations between explicit and implicit memory tests, between recollective and automatic retrieval processes, and between memorial states of awareness of past events all suggest that human memory is not a unitary faculty. Memory dissociations reflect the complex relationship between consciousness and memory. To understand such a complex relationship, any single level of analysis is not enough and may be misleading. A multi-level analysis was proposed. One of the most serious problems with the process-dissociation procedure is its failure to separate process level of analysis and memorial awareness level of analysis. One experiment was reported to support the above arguments.

This paper examines order effects and frequency learning in belief updating. We present an experiment that tests for the existence of order effects for actual decisions during frequency learning and for belief evaluations after frequency learning in a realistic tactical decision making task. The experiment revealed that (a) subjects showed order effects for actual decisions during frequency learning—an effect not reported previously and (b) subjects still showed order effects for belief evaluations even after having correctly learned most of the frequency information. We also present a simulation for the frequency learning behavior and some preliminary results of a simulation for the order effect, and suggest networks for potential combinations of the order effect and frequency learning.

Numerical tasks with Arabic numerals involve the integration of internal and external information and the interaction between perception and cognition. 2-digit number comparison task was selected to study these integration and interaction processes. To compare the magnitudes of two 2digit Arabic numerals, we can (1) compare them digitbydigit sequentially, (2) compare corresponding digits in parallel, or (3) encode them as an integrated representation and compare the whole numerical values. Previous studies showed that 2- digit comparison was holistic when target numerals were compared with a standard held in memory. In our experiment target numerals and standards were presented on the same external display at the same time. Instead of a holistic comparison, we found that 2-digit comparison was a combination of sequential and parallel comparisons. The implications of this discrepancy were discussed in terms of the interplay between perception and cognition.

When faced with a novel problem, people can sometimes decide what to do by imagining alternative sequences of actions and then taJdng the sequence that solves the problem. In many problems, however, various constraints, such as working memory capacity, limit the amount of internal lookahead that people can do. This paper describes Bottom-Up Recognition Learning (BURL), a model of limited-lookahead learning based on final first learning and knowledge compilation. In BURL, knowledge compilation of limited-lookahead search over successive problemsolving trials transfers knowledge from the leaf nodes of a problem space to the top node. Two experiments test BURL'S predictions. The first compares the Soar implementation of BURL to human subjects learning to play two Tlc-Tac-Toe isomorphs. This experiment shows that BURL can account for learning that occurs when subjects can perform a limited lookahead. The second experiment studies transfer between two strategy acquisition tasks for one isomorph. This experiment shows that BURL must be used in conjunction with other learning methods to fully explain skill acquisition on limited lookahead tasks.

Most graphic and tabular displays are relational information displays—displays that represent relational information, which is a relation on a set of dimensions. In this paper, we argue that relational information displays are distributed representations—representations that are distributed cross the internal mind and the external environment, and display-based tasks are distributed cognitive tasks—tasks that require the interwoven processing of internal and external information. The basic components of relational information displays are dimensions. Through a theoretical analysis of dimensional representations, we identified four major factors that affect the representational efficiencies of relational information displays: the distributed representation of scale information, the relation between psychological and physical measurements, the interaction between dimensions, and the visual and spatial properties of dimensions. Based on the representational analysis of relational information displays, we proposed a representational taxonomy of relational information displays. This taxonomy can classify most types of relational information displays. In addition, it can be used as a theoretical framework to study the empirical issues of relational information displays in a systematic way.

In this paper, we study the representationalproperties of numeration systems. W e argue thatnumeration systems are distributed representa-tions—representations that are distributedacross the internal mind and the external envi-ronment. W e analyze number representations atfour levels: dimensionality, dimensional repre-sentations, bases, and symbol representations.The representational properties at these fourlevels determine the representational efficien-cies of numeration systems and the performanceof numeric tasks. From this hierarchical struc-ture, we derive a cognitive taxonomy that canclassify most numeration systems.

In these studies I examine the role of distributed cognition in problem solving. The major hypothesis explored is that intelligent behavior results from the interaction of internal cognition, external objects, and other people, where a cognitive task can be distributed among a set of representations, some internal and some external. The Tower of Hanoi problem is used as a concrete example for these studies. In Experiment 1 I examine the effects of the distribution of internal and external representations on problem solving behavior. Experiments 2 and 3 focus on the effects of the structural change of a problem on problem solving behavior and how these effects depend on the nature of the representations. The results of all studies show that distributed cognitive activities are produced by the interaction among the internal and external representations. External representations are not simply peripheral aids. They are an indispensable part of cognition. Two of the factors determining the performance of a distributed cognitive system are the structure of the abstract problem space and the distribution of representations across an intemal mind and the external world.