Toward a theory of human memory: Data structures and access processes

1994 ◽  
Vol 17 (4) ◽  
pp. 655-667 ◽  
Author(s):  
Michael S. Humphreys ◽  
Janet Wiles ◽  
Simon Dennis

AbstractStarting from Marr's ideas about levels of explanation, a theory of the data structures and access processes in human memory is demonstrated on 10 tasks. Functional characteristics of human memory are captured implementation-independently. Our theory generates a multidimensional task classification subsuming existing classifications such as the distinction between tasks that are implicit versus explicit, data driven versus conceptually driven, and simple associative (two-way bindings) versus higher order (threeway bindings), providing a broad basis for new experiments. The formal language clarifies the binding problem in episodic memory, the role of input pathways in both episodic and semantic (lexical) memory, the importance of the input set in episodic memory, and the ubiquitous calculation of an intersection in theories of episodic and lexical access.

2013 ◽  
Vol 4 (1) ◽  
pp. 32-64 ◽  
Author(s):  
Elisa C. Castro ◽  
Ricardo R. Gudwin

In this paper the authors present the development of a scene-based episodic memory module for the cognitive architecture controlling an autonomous virtual creature, in a simulated 3D environment. The scene-based episodic memory has the role of improving the creature’s navigation system, by evoking the objects to be considered in planning, according to episodic remembrance of earlier scenes testified by the creature where these objects were present in the past. They introduce the main background on human memory systems and episodic memory study, and provide the main ideas behind the experiment.


2007 ◽  
Author(s):  
Paul S. Merritt ◽  
Adam Cobb ◽  
Luke Moissinac ◽  
Corpus Christi ◽  
Elliot Hirshman

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 278-279
Author(s):  
Feilong Wang ◽  
Shijie Li ◽  
Kaifa Wang ◽  
Yanni Yang

Abstract Older adults with subjective memory complaints (SMCs) are at increased risk for episodic memory decline. Episodic memory decline is an important predictor of objective memory impairment (one of the earliest symptoms of Alzheimer’s disease) and an often-suggested criterion of successful memory aging. Therefore, it is important to explore the determinant factors that influence episodic memory in older adults with SMCs. Roy adaptation model and preliminary evidence suggest that older adults with SMCs undergo a coping and adaptation process, a process influenced by many health-related risks and protective factors. This study aimed to explore the relationship between coping capacity and episodic memory, and the mediating role of healthy lifestyle between coping capacity and episodic memory in a sample of 309 community-dwelling older adults with SMCs. Results from the structural equation modeling showed that coping capacity directly affects episodic memory (r=0.629, p<0.001), and there is a partial mediating effect (60.5%) of healthy lifestyle among this sample of older adults with SMCs. This study demonstrates that coping capacity and adaptation positively correlate with episodic memory in older adults with SMCs, and that these correlations are mediated by healthy lifestyle. The results suggest that older adults with poor coping capacity should be assessed and monitored regularly, and clear lifestyle-related interventions initiated by healthcare providers that promote healthy lifestyles may effectively improve coping capacity and episodic memory in this population group. Note: First author: Feilong Wang, Co-first author: Shijie li, Corresponding author: Yanni Yang


Author(s):  
Catherine M. Sweeney-Reed ◽  
Lars Buentjen ◽  
Jürgen Voges ◽  
Friedhelm C. Schmitt ◽  
Tino Zaehle ◽  
...  

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.


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