Representational Systems Theory: A Unified Approach to Encoding, Analysing and Transforming Representations
Daniel Raggi, Gem Stapleton, Mateja Jamnik, Aaron Stockdill, Grecia, Garcia Garcia, Peter C-H. Cheng

TL;DR
This paper introduces Representational Systems Theory, a comprehensive framework for encoding, analyzing, and transforming various representations across different systems using a unified approach.
Contribution
It presents a novel, universal theory that encodes representations from syntax and entailment perspectives, enabling structural transformations without system-specific algorithms.
Findings
Allows structural transformation of representations between systems
Supports partial transformations when full algorithms are not available
Eliminates the need for system-specific transformation algorithms
Abstract
The study of representations is of fundamental importance to any form of communication, and our ability to exploit them effectively is paramount. This article presents a novel theory -- Representational Systems Theory -- that is designed to abstractly encode a wide variety of representations from three core perspectives: syntax, entailment, and their properties. By introducing the concept of a construction space, we are able to encode each of these core components under a single, unifying paradigm. Using our Representational Systems Theory, it becomes possible to structurally transform representations in one system into representations in another. An intrinsic facet of our structural transformation technique is representation selection based on properties that representations possess, such as their relative cognitive effectiveness or structural complexity. A major theoretical barrier to…
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Taxonomy
TopicsDNA and Biological Computing
