On levels of cognitive modeling

Sun, Ron; Coward, L. Andrew; Zenzen, Michael

doi:10.1080/09515080500264248

Cited by 79 publications

(45 citation statements)

References 38 publications

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“…Natural selection will also favour brains that can learn with the least accidental interference between prior and later learning, that can be built from DNA "blueprints" with few errors, and that can recover from component failures and damage. There are therefore pressures exerted by natural selection on brains that are analogous with the resource limitation, modifiability, constructability, and repairability considerations for computational systems, making it probable that analogous modular hierarchies in human mind/brains do exist, and furthermore, such modular hierarchies can in effect operate as hierarchies of description as mentioned before (see also Coward and Sun 2004, Sun et al 2005, Sun 2002). …”

Section: Theories In the Physical Sciencesmentioning

confidence: 99%

“…The problem would be that such a model would simply be another incomprehensible cognitive system. The requirement for an effective theory, we believe, is to find a hierarchy of descriptions such that small elements of a psychological description can be mapped into a more detailed level, small elements of that more detailed level into a yet more detailed level, and so on, down to descriptions at the neuron level or below [Sun et al 2005]. It is accepted that descriptions at higher levels would be often more approximate, but the approximations would be well understood (relatively speaking) and there often would be rules identifying when and how to shift to a more detailed level to achieve a required level of accuracy.…”

Section: Theories In the Physical Sciencesmentioning

confidence: 99%

“…Another is the recommendation architecture, which is divided into two subsystems, one defining and detecting conditions in the information available to the system, the other interpreting conditions as behavioural recommendations, and adjusting recommendation weights on the basis of rewards [Coward, 2001;2005]. Both models can provide descriptions of "conscious" processes at levels intermediate between high-level psychological descriptions and detailed descriptions in terms of neuronal processes (Sun et al 2005).…”

Section: General Form Of a Scientific Theory Of Consciousnessmentioning

confidence: 99%

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Hierarchical approaches to understanding consciousness

Coward

Sun

2007

Neural Networks

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There has been much discussion of what a scientific theory of consciousness would look like, and even whether such a theory is possible. Some common misunderstandings of the nature of theories (e.g., in the physical sciences) have confused the discussion of theories concerning consciousness. Theories in the physical sciences establish hierarchies of descriptions that relate high-level descriptions of macro-level phenomena to detailed-level descriptions at a micro level. Detailed descriptions are usually more accurate but information-dense and therefore often beyond human comprehensibility (unless limited to tiny segments of a macrolevel phenomenon). High-level descriptions are usually much less information-dense but more approximate. The ability to map between levels of description, and in particular the understanding of when a shift from a higher-level to a more detailed description is needed to achieve a desired degree of accuracy, is fundamental to an effective theory in any field. The form of such a theory of consciousness is sketched, and the limitations of some alternative approaches described. IntroductionThere are a range of possible approaches aimed at understanding consciousness. At one extreme, there has been debate over whether a scientific theory of consciousness is possible in principle [e.g. Chalmers 1995]. Another type of approach has been the creation of models that describe cognitive operations regarded as being conscious, but with limited consideration for how physiology could support the processes required by the model. Computer implementations of some of these models have been attempted [e.g. Franklin et al 1999, Sun 1999]. Yet another approach has been to look for physiological activity that discriminates between conscious and unconscious states, the so-called "neural correlates of consciousness" [e.g. Rees et al, 2002, Crick et al 1998]. Yet another approach has been to claim that understanding of consciousness is only possible with reference to quantum mechanics [Penrose 1994]. Furthermore, there have been extensive debates over what phenomena should actually be labeled "conscious" [e.g. Block 1995]. The end result has been considerable metatheoretical confusion.For several centuries, the physical sciences have been regarded as the paradigm for valid scientific theories. We believe that much of the confusion over scientific understanding of consciousness derives from misunderstanding of what theories in the physical sciences actually deliver, and once these misunderstandings are cleared away, the form which a theory of consciousness must take becomes clearer. There are some good questions about whether a scientific theory of consciousness is possible, but these questions are in fact more empirical than philosophical, and relate to whether the brain is organized in such a way that understanding can occur within the limits of human information handling capabilities.There are some significant similarities between theories in the physical sciences and the theoretical techniques by whi...

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Section: Theories In the Physical Sciencesmentioning

confidence: 99%

Section: Theories In the Physical Sciencesmentioning

confidence: 99%

Section: General Form Of a Scientific Theory Of Consciousnessmentioning

confidence: 99%

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Hierarchical approaches to understanding consciousness

Coward

Sun

2007

Neural Networks

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“…What constitutes a mental representation is not completely obvious. Multiple levels of explanation are common in the cognitive sciences (Marr 1982;Sun, Coward, and Zenzen 2005). To take one example, models developed in the ACT-R cognitive architecture (Anderson et al 2004;Anderson, Fincham, Qin, and Stocco 2008) refer to representations of declarative memories, goals, and the current focus of attention and to rules for transforming these representations.…”

Section: What Explanations Do We Expect From Statistical and Cognitivmentioning

confidence: 99%

Statistical models as cognitive models of individual differences in reasoning

Fugard

Stenning

2013

Argument & Computation

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There are individual differences in reasoning which go beyond dimensions of ability. Valid models of cognition must take these differences into account, otherwise they characterise group mean phenomena which explain nobody. The gap is closing between formal cognitive models, which are designed from the ground up to explain cognitive phenomena, and statistical models, which traditionally concern the more modest task of modelling relationships in data. This paper critically reviews three illustrative statistical models of individual differences in reasoning which embed some notion of cognitive process. Although the models are each developed in different frameworks, it is shown that they are more similar than would first appear. The cognitive meaning of elements in the example models is explored and some sketches are developed for future directions of research.

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“…A hierarchy of descriptions of the same phenomenon from psychological to physiological is needed, with clear mapping between the levels (Coward and Sun 2004;Sun et al 2005). At any one level, it must be possible to describe how at each point in time the observed situation causes the situation at the next point in time, in other words, descriptions must be causal.…”

Section: Introductionmentioning

confidence: 99%

Modelling Memory and Learning Consistently from Psychology to Physiology

Coward

2010

Perception-Action Cycle

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Natural selection pressures have resulted in the physical resources of the brain being organized into modules that perform different general types of information processes. Each module is made up of submodules performing different information processes of the general type, and each submodule is made up of yet more detailed modules. At the highest level, modules correspond with major anatomical structures like the cortex, hippocampus, basal ganglia, cerebellum etc. In the cortex, for example, the more detailed modules include areas, columns, neurons, and a series of neuron substructures down to molecules. Any one memory or learning phenomenon requires many information processes performed by many different anatomical structures. However, the modular structure makes it possible to describe a memory phenomenon at a high (psychological) level in terms of the information processes performed by the major anatomical structures. The same phenomenon can be described at each level in a hierarchy of more detailed descriptions, in terms of the information processes performed by anatomical substructures. At higher levels, descriptions are approximate but can be mapped to more detailed, more precise descriptions as required down to neuron levels and below. The total information content of a high level description is small enough that it can be fully understood. Small parts of a high level phenomenon, when described at a more detailed level, also have a small enough information content to be understood. The information processes and resultant hierarchy of descriptions therefore make it possible to understand cognitive phenomena like episodic, semantic or working memory in terms of neuron processes via a series of intermediate levels of description.

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On levels of cognitive modeling

Cited by 79 publications

References 38 publications

Hierarchical approaches to understanding consciousness

Hierarchical approaches to understanding consciousness

Statistical models as cognitive models of individual differences in reasoning

Modelling Memory and Learning Consistently from Psychology to Physiology

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