8 research outputs found
Dissecting Representations
Choosing effective representations for a problem and for the person solving it has benefits, including the ability or inability to solve it. We previously devised a novel framework consisting of a language to describe representations and computational methods to analyse them in terms of their formal and cognitive properties. In this paper we demonstrate the application of this framework to a variety of notations including natural languages, formal languages, and diagrams. We show how our framework, and the analysis of representations that it enables, gives us insight into how and why we can select representations which are appropriate for both the task and the user
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How to (Re)represent it?
Choosing an effective representation is fundamental to the ability of the representationâs user to exploit it for the intended purpose. The major contribution of this paper is to provide a novel, flexible framework, rep2rep, that can be used by AI systems to recommend effective representations. What makes an effective representation is determined by whether it expresses the necessary information, supports the execution of tasks, and reflects the userâs cognitive abilities. In general, there is no single âmost effectiveâ representation for every problem and every user, which makes it difficult to choose one from the plethora of possible representations. To address this, rep2rep includes: a domain-independent language for describing representations, algorithms that compute measures of informational suitability and cognitive cost, and uses these measures to recommend representations. We demonstrate the application of rep2rep in the probability domain. Importantly, our framework provides the foundations for personalised interaction with AI systems in the context of representation choice
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Considerations in Representation Selection for Problem Solving: A Review
Choosing how to represent knowledge effectively is a long-standing open problem. Cognitive science has shed light on the taxonomisation of representational systems from the perspective of cognitive processes, but a similar analysis is absent from the perspective of problem solving, where the representations are employed. In this paper we review how representation choices are made for solving problems in the context of theorem proving from three perspectives: cognition, heterogeneity, and computational demands. We contrast the different factors that are most important for each perspective in the context of problem solving to produce a list of considerations for developers of problem solving tools regarding representations that are appropriate for particular users and effective for specific problem domains
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Inspection and Selection of Representations
We present a novel framework for inspecting representations and encoding their formal properties. This enables us to assess and compare the informational and cognitive value of different representations for reasoning. The purpose of our framework is to automate the process of representation selection, taking into account the candidate representationâs match to the problem at hand and to the userâs specific cognitive profile. This requires a language for talking about representations, and methods for analysing their relative advantages. This foundational work is first to devise a computational end-to-end framework where problems, representations, and userâs profiles can be described and analysed. As AI systems become ubiquitous, it is important for them to be more compatible with human reasoning, and our framework enables just that.EPSR
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The Sound-Poetry of the Instability of Reality: Mimesis and the Reality Effect in Music, Literature, and Visual Art
This paper uses the concept of mimesis to clarify the debate concerning the representation of reality in music. Specifically, this study defines the audio reality effect and the three main practices of realism as a way of understanding mimetic practices in multiple artistic media, in particular regarding the multimedia works of the "Landscape series." After addressing the historical debates concerning mimesis, this study develops a framework for the understanding of mimesis in sound by addressing the writings of Weiss, Baudrillard, Barthes, Deleuze, and Prendergast and by examining mimetic practices in 19th-century European painting and multimedia performance works. The audio reality effect is proposed as a meaningful translation of Roland Barthes' literary reality effect to the sonic realm. The main trends of realist practice are applied to electroacoustic music and soundscape composition using the works and writings of Emmerson, Truax, Wishart, Risset, Riddell, Smalley, Murray Schafer, Fischman, Young, and Field. Lastly, this study mimetically analyzes "2 seconds / b minor / wave" by Michael Pisaro and Taku Sugimoto and the works of the "Landscape series" in order to demonstrate the relevance of mimesis for understanding current musical practice
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What constitutes an effective representation?
This paper presents a taxonomy of 19 cognitive criteria for judging what constitutes effective representational systems, particularly for knowledge rich topics. Two classes of cognitive criteria are discussed. The first concerns access to concepts by reading and making inferences from external representations. The second class addresses the generation and manipulation of external representations to fulfill reasoning or problem solving goals. Suggestions for the use of the classification are made. Examples of conventional representations and Law Encoding Diagrams for the conceptual challenging topic of particle collisions are provided throughout