Theories Of Cognitive Architecture Research Articles

Comparing memory capacity across stimuli requires maximally dissimilar foils: Using deep convolutional neural networks to understand visual working memory capacity for real-world objects.

The capacity of visual working and visual long-term memory plays a critical role in theories of cognitive architecture and the relationship between memory and other cognitive systems. Here, we argue that before asking the question of how capacity varies across different stimuli or what the upper bound of capacity is for a given memory system, it is necessary to establish a methodology that allows a fair comparison between distinct stimulus sets and conditions. One of the most important factors determining performance in a memory task is target/foil dissimilarity. We argue that only by maximizing the dissimilarity of the target and foil in each stimulus set can we provide a fair basis for memory comparisons between stimuli. In the current work we focus on a way to pick such foils objectively for complex, meaningful real-world objects by using deep convolutional neural networks, and we validate this using both memory tests and similarity metrics. Using this method, we then provide evidence that there is a greater capacity for real-world objects relative to simple colors in visual working memory; critically, we also show that this difference can be reduced or eliminated when non-comparable foils are used, potentially explaining why previous work has not always found such a difference. Our study thus demonstrates that working memory capacity depends on the type of information that is remembered and that assessing capacity depends critically on foil dissimilarity, especially when comparing memory performance and other cognitive systems across different stimulus sets.

Feedback from moral philosophy to cognitive science

A popular argument form uses general theories of cognitive architecture to motivate conclusions about the nature of moral cognition. This paper highlights the possibility for modus tollens reversal of this argument form. If theories of cognitive architecture generate predictions for moral cognition, then tests of moral thinking provide feedback to cognitive science. In certain circumstances, philosophers' introspective attention to their own moral deliberations can provide unique data for these tests. Recognizing the possibility for this sort of feedback helps to illuminate a deep continuity between the disciplines.

A computational unification of cognitive behavior and emotion

Existing models that integrate emotion and cognition generally do not fully specify why cognition needs emotion and conversely why emotion needs cognition. In this paper, we present a unified computational model that combines an abstract cognitive theory of behavior control (PEACTIDM) and a detailed theory of emotion (based on an appraisal theory), integrated in a theory of cognitive architecture (Soar). The theory of cognitive control specifies a set of required computational functions and their abstract inputs and outputs, while the appraisal theory specifies in more detail the nature of these inputs and outputs and an ontology for their representation. We argue that there is a surprising functional symbiosis between these two independently motivated theories that leads to a deeper theoretical integration than has been previously obtained in other computational treatments of cognition and emotion. We use an implemented model in Soar to test the feasibility of the resulting integrated theory, and explore its implications and predictive power in several task domains.

Inferencing From Spatial Information

Making inferences on the basis of spatial information, such as taking shortcuts, and reasoning with graphs and diagrams, is a commonality between very different tasks of spatial cognition. This paper discusses three processes of reasoning about space: integrating pairwise relations, integrating different spatial relations from different information types, and aligning relational structures. The final section of the paper poses the question whether these three processes are common to both small-scale and large-scale spatial reasoning, and if so, how those commonalities might inform our theories of cognitive architecture.

Polysemy and cognition

Polysemy - the existence of multiple but related meanings for a single form - has always been problematic for purely structural accounts of meaning. When it is viewed from a cognitive perspective, however, it emerges as a natural, indeed necessary consequence of the human ability to think flexibility. If we synthesize three approaches: John Anderson's theory of cognitive architecture, Sperber and Wilson's concept of relevance, and Lakoff and Johnson's theory of image schemas, it is possible to account for many of the properties of polysemy. Essentially, polysemy is an effect of relevance: of the human ability to select the interpretation which maximizes useful information while minimizing processing cost. An account in these terms helps to address a number of unresolved problems. Polysemy has been problematic because it seemed to fall on the border between category identity and category distinctness. This gradient can be treated in terms of relevance: two items belong to distinct categories only to the extent that shared information is relevant and contrasting information is irrelevant. Polysemy also displays clear asymmetries both in its distribution and in its interaction with anaphoric phenomena. These can be explained by asymmetries of activation spread through image schematic structure; where activation spread is facilitated, processing costs are lowered, increasing relevance, and hence facilitating both polysemy and the recovery of anaphoric reference.