Review of Dynamical Cognitive Science, Ward, L.M

1995

Recently, a new approach to modeling cognitive phenomena has been gaining recognition: the dynamical systems approach. Proponents of this theory claim to have identified a new paradigm for the study of cognition which is superior to both symbolicism and connectionism.

2011

Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that this DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN), are the ones that are causing trouble in the philosophy of science speculation, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonability of a possibility.

Mind Reading: introductory selections on cognitive …

Dr Neville Buch ABN: 86703686642, 2025

This paper presents a model of dynamic cognition. That model is humanly produced in the first section. The second section is the A.I. answer to the command to explain how attitudes and values work in cognition, as a comparison to the Buch’s The Dynamic of Cognition Model. The last section of the paper is a bibliography of readings on the subject.

Unified Dynamic Model of the Mind: A Comprehensive Framework for Cognitive Science, 2025

Abstract The Unified Dynamic Model of the Mind presents a comprehensive framework for understanding cognitive processes as dynamic, interrelated, and continuously evolving. This model integrates principles from cognitive science, neuroscience, psychology, and artificial intelligence to explore the intricate interactions between perception, memory, reasoning, and emotional dynamics. By bridging conscious and unconscious processes, the framework provides insights into how mental representations adapt in response to internal and external stimuli. Developed collaboratively through the Storm Platform at Stanford University, this work highlights practical applications in fields such as education, healthcare, and AI development. It emphasizes the role of cultural and environmental factors in shaping cognition while offering innovative solutions for addressing individual differences and decision-making processes. The integration of computational models and dynamic systems theory underscores the model's potential for advancing both theoretical understanding and practical applications in cognitive science and beyond. This research represents a significant step toward unifying disparate cognitive theories into a cohesive framework, paving the way for future exploration and interdisciplinary collaboration.

2001

Mental models of dynamic systems, MMDS Definition Cognitive processes are any mental activity that acquires, stores, transforms, reduces, elaborates, or uses knowledge. Cognitive processes are also referred to as cognition.

Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN) are the ones that are causing trouble in the philosophy of science, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonableness of a possibility.

Dynamic Cognitive Processes, 2005

This brief chapter provides an overview of the book. A sketch is provided of the sharp contrast between the popular view that cognition is relatively static and the view in the discipline that cognition is highly dynamic. This provides the high-level theme of the entire book. Weaving throughout the book are several other more specific themes, notably the roles of consciousness and of inhibition in cognition, and the complimentary behavioural and neuroscience approaches. Linkages across chapters are described, and a brief synopsis of each chapter is provided.

2007

Approaches to cognitive science have been socially divided into dynamical and computational camps. We break down the dynamical approach into finer components, suggesting a new taxonomy of dynamical approaches to cognition and questioning the logical unity of the dynamical school. We dispel some confusions surrounding the concepts of dynamical systems, computation, and the relation between the two. We introduce and argue for the notion of "cognition as it could be" and show its value in analysing the dynamicists' account of time.

Unified dynamic model of mind, 2025

Introduction to the Unified Dynamic Model of the Mind (UDMM) Traditional cognitive models have significantly contributed to our understanding of human thought processes. Notably, Kahneman's dual-system theory, which distinguishes between rapid, intuitive processing (System 1) and slower, analytical reasoning (System 2), has provided valuable insights into how we make judgments and decisions [Introduction section of the paper]. These models often delineate distinct cognitive functions and their characteristics. However, a limitation of many of these established frameworks is their tendency to be descriptive and relatively static in their representation of mental processes [Introduction section of the paper]. This can lead to a view of cognition as a collection of separate modules or stages, potentially overlooking the continuous and interactive nature of how the mind operates. The Unified Dynamic Model of the Mind (UDMM) emerges as a response to these limitations, proposing a more fluid and interconnected perspective on cognition. The Unified Dynamic Model of the Mind (UDMM) presents a comprehensive framework that conceptualizes mental processes as inherently dynamic, predictive, and continuously self-updating. At its core, UDMM posits that the human mind actively constructs an internal model of reality. This construction is not a passive reception of sensory information but rather an active process of generating predictions about the world and subsequently validating or adjusting these predictions based on ongoing sensory and emotional input. By integrating sensory, emotional, and cognitive processes into a cohesive system, UDMM offers a unified approach to understanding a wide range of mental functions, including perception, memory, decision-making, and behavior. The implications of this framework are far-reaching, potentially impacting fields such as artificial intelligence, education, and cognitive therapy. This report will delve into the core principles of UDMM, contextualize it within the broader landscape of cognitive science by examining its relationship with predictive processing and dual-system theories, explore its potential applications across various domains, and offer a critical evaluation of its strengths and limitations. 2. Core Principles of the Unified Dynamic Model of the Mind (UDMM) Elaborated At the heart of UDMM lies the principle of internal model construction. The mind is viewed as continuously building and refining an internal "map" or catalog of the environment. This internal representation is not solely based on raw sensory inputs but also incorporates emotional responses and past experiences. This suggests that UDMM posits a rich and multifaceted mental representation of the world, going beyond simple sensory data to include affective and experiential dimensions that shape our understanding of reality [Insight 3]. A central tenet of UDMM is predictive processing. Rather than passively waiting for sensory information to arrive, the mind actively generates predictions about the incoming data. When the