Learning and Consolidation as Re-representation: Revising the Meaning of Memory.

Geraint A Wiggins,Abdelrahman Sanjekdar

doi:10.3389/fpsyg.2019.00802

Abstract

In this Hypothesis and Theory paper, we consider the problem of learning deeply structured knowledge representations in the absence of predefined ontologies, and in the context of long-term learning. In particular, we consider this process as a sequence of re-representation steps, of various kinds. The Information Dynamics of Thinking theory (IDyOT) admits such learning, and provides a hypothetical mechanism for the human-like construction of hierarchical memory, with the provision of symbols constructed by the system that embodies the theory. The combination of long-term learning and meaning construction in terms of symbols grounded in perceptual experience entails that the system, like a human, be capable of memory consolidation, to manage the complex and inconsistent structures that can result from learning of information that becomes more complete over time. Such consolidation changes memory structures, and thus changes their meaning. Therefore, memory consolidation entails re-representation, while re-representation entails changes of meaning. Ultimately, the theory proposes that the processes of learning and consolidation should be considered as repeated re-representation of what is learned.

Highlights

REPRESENTATION AND RE-REPRESENTATIONThis paper is about representation and re-representation, from the perspective of computational modeling of cognitive process.The word “representation” is problematic in the interdisciplinary context of this article, because its meaning to computer scientists differs from its meaning to psychologists
In computer science and artificial intelligence, there is an element to the representation of knowledge which is usually referred to as “semantics.” This is strongly related to the idea of “semantic memory” in psychology and cognitive science, but different: the semantics is a way of writing down the meanings expressed using the representation in such a way as to formally and consistently be able to compute with them
Each book is loaded into Information Dynamics of Thinking theory (IDyOT), the lowest representation level being letters, and the resulting IDyOT sequential memory is examined to evaluate the contribution of the successive layers

Summary

Introduction

REPRESENTATION AND RE-REPRESENTATIONThis paper is about representation and re-representation, from the perspective of computational modeling of cognitive process.The word “representation” is problematic in the interdisciplinary context of this article, because its meaning to computer scientists differs from its meaning to psychologists. The difference will bear strongly on the explanatory nature of the model proposed. In both fields, a representation (cognitive or computational) is a description of a thing, concept or state of affairs, respectively either in the memory of a computer or in the memory of a brain. In computer science and artificial intelligence, there is an element to the representation of knowledge which is usually referred to as “semantics.” This is strongly related to the idea of “semantic memory” in psychology and cognitive science, but different: the semantics is a way of writing down the meanings expressed using the representation (scheme) in such a way as to formally and consistently be able to compute with them. Other on-going work in the area relates to the idea of “free energy” (Friston, 2010) and intrinsic motivation (Schmidhuber, 2010)

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