Attention is thought to be a part of a larger cluster of mecha-nisms that serve to orient a cognitive system, to filter contentswith respect to their task relevance, and to devote more com-putation to certain options than to others. All these activitiesproceed under the plausible assumption that not all informationcan be or ought to be processed for a system to satisfice in anever changing world. In this paper, we describe an attention-centric cognitive system called ARCADIA that demonstratesthe orienting, filtering, and resource-skewing functions men-tioned above. The demonstration involves maintaining focuson cognitive tasks in a dynamic environment. While ARCA-DIA carries out a task, limits on its attentional capacity resultin “inattentional blindness” under circumstances analogous tothose where people fail to perceive otherwise salient stimuli.

With few exceptions, architectural approaches to modeling cognition have historically emphasized what happens in the mind following the transduction of environmental signals into percepts. To our knowledge, none of these architectures implements a sophisticated, general theory of human attention. In this paper we summarize progress to date on a new cognitive architecture called ARCADIA that gives a central role to attention in both perception and cognition. First, we give an overview of the architecture, comparing it to other approaches when appropriate. Second, we present a model of incremental object construction and property binding in ARCADIA using the well known change blindness phenomena to illustrate the time course of object perception and its dependence on attention. Finally, we discuss near-term challenges and future plans

Quantity can be expressed in a variety of ways and at dif-ferent levels of precision. One factor that influences numer-ical description of elements in a visual scene is how long thescene is observed. We extend a previous incremental modelof numerical perception to model quantified description undertime constraints. Our extended model predicts that as presen-tation duration decreases and as the quantity of items to beenumerated increases, the frequency of inexact quantifiers willincrease. We conducted two human subject elicitation stud-ies to test these predictions. Our findings were consistent withour model’s predictions. Additionally, we demonstrate that ournovel model of incremental numerical perception and quanti-fied description closely predicts the precise proportion of exactnumerical responses generated by in these experiments.

Enumeration of canonical patterns (e.g., faces of six-sideddice) has generally been characterized by researchers as aholistic process, in which all items are perceived collectively.In previous work, based on a holistic processing view of enu-meration by pattern recognition, we predicted that enumera-tion of canonical forms would not be significantly affected byattentional load. In this paper, we present the results from twoexperiments designed to test this prediction using a divided-attention paradigm. In contrast to our predictions, enumerationof canonical patterns was disrupted by attentional load. Fur-thermore, enumeration of patterns under high attentional loadshowed evidence of conflation between patterns with similarcontours, providing evidence against a holistic processing ac-count of canonical pattern recognition.

Current psychological accounts of causal representation and reasoning do not capture phenomena related to causation by omission (e.g., “The absence of breathing causes death”), with one exception (Wolff, Barbey, & Hausknecht, 2010). We describe a novel theory of omissive causation that posits that people build discrete mental simulations – mental models – of causal relations (Goldvarg & Johnson-Laird 2001). The theory states that causes by omission refer to a set of temporally ordered models of possibilities. Reasoners tend to focus on only one of those models, i.e., the possibility in which breathing does not occur and death subsequently does. Likewise, the theory posits that reasoners distinguish between omission in the context of causation, enabling conditions, and prevention. We describe some initial predictions made by the model-based account, contrast it with an alternative psychological theory based on the transmission of causal forces, and set out directions for further research.

Recent studies in the perception of numerosity have indicatedthat subitizing (the rapid and accurate enumeration of smallquantities) requires attention. We present a novel computa-tional model of enumeration in which attention unifies dis-tinct processes of numerosity approximation, subitizing, andexplicit counting. We demonstrate how this model accountsfor both the reaction time results from the subitizing literatureand the effects of attentional load on subitizing accuracy.