How is shape represented during spatial tasks such as mental rotation? This research investigated the format of mental representations of 3-D shapes during mental rotation. Specifically, we tested the extent to which visual information, such as color, is represented during mental rotation using methods ranging from reaction time studies, verbal protocol analysis, and eyetracking. Another set of studies examined whether people use piecemeal or holistic strategies to rotate complex objects. Results show that individuals with good rotation ability do not represent color during mental rotation and rotate whole shapes; whereas poor rotators do represent color and rotate individual pieces of the shape using piecemeal strategies. This work contributes to theories about cognitive shape processing by showing that different information processing strategies may be one cause of individual differences in mentally rotation performance.

A human subject experiment was conducted to investigate caffeine’s effect on appraisal and performance of a mental serial subtraction task. Serial subtraction performance data was collected from three treatment groups: placebo, 200, and 400 mg caffeine. The data were analyzed by caffeine treat ment group and how subjects appraised the task (as challenging or threatening). A cognitive model of the serial subtraction task was developed. The model was fit to the human performance data using a parallel genetic algorithm. How the model’s parameters change to fit the data suggest how cognition changes due to caffeine and appraisal. Over all, the cognitive modeling and optimization results suggest that the speed of vocalization varies the most along with changes to declarative memory. This approach provides a way to compute how cognitive mechanisms change due to moderators.

Time perception and inferences there from are of critical importance to many autonomous agents. But time is not perceived directly by any sensory organ. We argue that time is constructed by cognitive processes. Here we present a model for time perception that concentrates on succession and duration, and that generates these concepts and others, such as continuity, immediate present duration, and lengths of time. These concepts are grounded through the perceptual process itself. The LIDA cognitive model is used to illustrate these ideas.

This paper describes some functionalities and features of the Maryland Virtual Patient (MVP) environment. MVP models the process of disease progression, diagnosis and treatment in virtual patients who are endowed with a “body,” a simulation of their physiological and pathological processes, and a “mind,” a set of capabilities of perception, reasoning and action that allow the virtual patient to exhibit independent behavior, participate in a natural language dialog, remember events, hold beliefs about other agents and about specific object and event instances, make decisions and learn.

In this paper, we present a cognitive model of frequency-based decision-making applied to the task of landmine detection. The model is implemented in the ACT-R cognitive architecture and is strongly constrained by the cognitive primitives of the architecture. We then generalize the model to another task in the domain of macroeconomic decision-making using the same architecture, pursuing theoretical parsimony. We describe each model's representation requirements, assess their fits to the data, and analyze their performance scaling as a function of task and architectural parameters. Efforts to generalize the landmine detection model to macroeconomic decision making showed that reasonable fits to the macro-economic performance data could be achieved by models based either on procedural knowledge or declarative knowledge. This finding underscores the importance of distinguishing between processing strategies employed to execute tasks. Such detail appears needed to understand the neural foundations of frequency-based decision-making.

An exception is which tracks the extent to which material has our Degrees of Grounding model [Roque and Traum, 2008], reached mutual belief in a dialogue, and conduct which provides a more detailed description of the extent to experiments in which the model is used to manage which material has become a part of the common ground during grounding behavior in spoken dialogues with a virtual a dialogue. In this paper we describe experiments in applying human. We show that the model produces improvements that model to handle explicit grounding behavior in in virtual human performance as measured a virtual human. We begin by describing the model and the by post-session questionnaires.

We evaluate conversational transcripts of deceptive speech using a sophisticated natural language processing tool called Coh-Metrix. Coh-Metrix is unique in that it tracks linguistic features based on social and cognitive factors. The results from Coh-Metrix are compared to linguistic features reported in previous independent deception research, which used a natural language processing tool called LIWC. The comparison provides converging validity for several linguistic features, and establishes new insights on deceptive language.

This paper presents an approach to creating flexible general-logic representations from language for use in high-level reasoning tasks in cognitive modeling.  These representations are grounded in a large-scale ontology and emphasize the need for semantic breadth at the cost of syntactic breadth.  The task-independent interpretation process allows task-specific pragmatics to guide the interpretation process. In the context of a particular cognitive model, we discuss our use of limited abduction for interpretation and show results of its performance.

Attempting to model human categorization and similarity judgements is both a very interesting but also an exceedingly difficult challenge. Some of the difficulty arises because of conflicting evidence whether human categorization and similarity judgements should or should not be modelled as to operate on a mental representation that is essentially metric. Intuitively, this has a strong appeal as it would allow (dis)similarity to be represented geometrically as distance in some internal space.

Attempting to model human categorization and similarity judgements is both a very interesting but also an exceedingly difficult challenge. Some of the difficulty arises because of conflicting evidence whether human categorization and similarity judgements should or should not be modelled as to operate on a mental representation that is essentially metric. Intuitively, this has a strong appeal as it would allow (dis)similarity to be represented geometrically as distance in some internal space.