Symbol emergence in design

A key step in mapping the more conceptual stages of design onto computational systems involves identifying a vocabulary and ontology. While a number of high-level ontologies have been proposed, these are difficult to ground in terms of actual design instances, and manual definitions of the symbols are often incomplete and difficult to maintain. As an alternative, we propose an ”infant designer” paradigm which abstracts patterns for the ”functionally feasible regions” (FFR) while evaluating many individual configurations in the design space. These learned FFR patterns (which may arise due to minimal levels of functional acceptability, or from optimization) often embody dependency relationships among the design parameters, i.e. the good designs lie along lower-dimensional manifolds in the design parameter space. We show how such manifolds exist in several design situations; each combination of the original design parameters may be thought of as a ”chunk”; the space of these chunks models only the ”good designs”. Next, we show how the patterns defined based on these chunks constitute image schemas, which may be implicit (e.g. the pattern for an FFR), or explicit (where the relationship is observable). These patterns or image schemas are incipient semantic model leading to symbols. We present examples of how such image schemas are arrived at with the help of universal motor design. 1 Efforts towards standardizing the design vocabulary Evolving a standardized vocabulary for design has emerged as an important focus in engineering design. Possible applications include developing design repositories [Bohm et al., 2005], computer assisted conceptual design [Gero and Fujii, 2000], etc. It is clear that vocabularies are structured, that is there are considerable relations between terms. Often, this is viewed as an ontology or as a structured relationship that captures a part of the semantics of these terms. One popular view of the engineering system considers the flow of energy, information, etc, and proceeds downward into detailed design. With its roots in value engineering ideas from the 1940s, these notions were seeded by the analysis in Pahl and Beitz [Pahl and Beitz, 19881996] and a particularly influential study by Welch and Dixon [Richard and Dixon, 1994], leading to modern ontological models like the widely used functional basis model [Hirtz et al., 2002] or implementations on ontology tools [Nanda et al., 2007; Szykman et al., 2001]. The above represents the human-engineered approach to defining symbols. This type of approach is initially tempting because it tends to meet immediate applications, but a long history in knowledge-based systems has shown it to be brittle, i.e. subject to failure under even minor deviations in the domain. In general, it may be that symbols are more meaningfully developed by abstracting from existing data. The novel contribution of this paper is to show that at least in certain types of design tasks, lower-dimensional surfaces are revealed by multi-objective optimization. The intrinsic dimensions in these pareto-surfaces might constitute one approach to obtaining “symbols” directly from experiential data as opposed to engineering them by programming definitions / rules. These approaches are detailed further in section 1.2 and section 3, but first we look more closely at the term “symbol”, and what is understood by its semantics. 1.1 The semantics of design symbols Unfortunately the term “symbol”, as it is used in the logic and computational theory is considerably different from its usage in cognitive linguistics and in everyday life. In the latter usage, symbols are imbued with meaning grounded on experience, whereas in the formal usage, it is merely a token constructed from some finite alphabet, and is related only to other such tokens. If we present an analogy, a blind man knows “red” is a different color from “blue” and “green” but his understanding of red is dramatically different from that of a sighted person, because the semantic pole is not connected to direct experience.On the other hand, “symbol” has come to be understood in cognitive science (and also traditionally in linguistics, e.g. de Saussure ( [De Saussure, 19161986]), as the tight binding of the of the psychological impression of the sound (the “phonological pole”) with the mental image of the meaning (the semantic pole) [Langacker, 1986]. The mental image or image schema includes all sorts of associations and