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A Creative Analogy Machine: Results and Challenges View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by MURAL - Maynooth University Research Archive Library A Creative Analogy Machine: Results and Challenges Diarmuid P. O’Donoghue Mark T. Keane Department of Computer Science, Department of Computer Science and Informatics, National University of Ireland Maynooth, University College Dublin, Co. Kildare, Ireland. Ireland. [email protected] [email protected] Abstract While Boden (1992) argues that analogy is effectively Are we any closer to creating an autonomous model of the lowest form of creativity (improbable), we argue that analogical reasoning that can generate new and creative analogical creativity should be seen a part of a cohesive analogical comparisons? A three-phase model of ana- human reasoning system. If the inferences mandated by an logical reasoning is presented that encompasses the analogy contradicts a fundamental belief, especially one phases of retrieval, mapping and inference validation. that has accrued many consequent implications, then re- The model of the retrieval phase maximizes its creativ- solving this contradiction might well involve the “shock ity by focusing on domain topology, combating the se- and amazement” of transformational creativity. As such, it mantic locality suffered by other models. The mapping appears that analogies may drive creativity at any of model builds on a standard model of the mapping Boden’s levels of creativity. Our creativity model is do- phase, again making use of domain topology. A novel validation model helps ensure the quality of the infer- main independent and does not include a pragmatic com- ences that are accepted by the model. We evaluated the ponent or domain context. So, as our model does not use ability of our tri-phase model to re-discover several h- domain-specific knowledge, arguably it cannot be easily creative analogies (Boden, 1992) from a background cast as improbable, exploratory or transformational crea- memory containing many potential source domains. tivity (Boden, 1992). The model successfully re-discovered all creative com- The current work was driven by three main aims. Firstly, parisons, even when given problem descriptions that we wished to assess the creative potential of a three-phase more accurately reflect the original problem – rather model of analogy. Secondly, we wished to assess the im- than the standard (post hoc) representation of the anal- pact of using differing knowledge bases upon the creative ogy. Finally, some remaining challenges for a truly potential of our analogy model. Finally, we wished to as- autonomous creative analogy machine are assessed. sess the wider implications of analogical models for com- putational creativity. Is a three-phase model either neces- Introduction sary or sufficient to function as an engine of creativity? Can such a model re-discover analogies considered to be Analogy has a long and illustrious history within creativity, creative by people? Since people often overlook analogies particularly within scientific and intellectual contexts (Gick and Holyoak, 1980) even when they are present, will (Brown, 2003). Many episodes of scientific creativity are such a model uncover many creative analogies or are crea- driven by analogical comparisons (Dunbar and Blanchette, tive analogies, in some way, different and rare? 2001), often involving image related analogies (Clement, We see the current model as being potentially useful in 2008). Much progress has been made in cognitive science three distinct ways, but for now we do not commit to using on modeling this analogical reasoning process (see below), it in one particular manner. Firstly, it could be used as a prompting the following questions. Are we any closer to simple model of creativity, yielding creative interpretations creating an autonomous model of the analogical reasoning for a presented problem. Secondly, it could be used as a that can generate new creative analogies? What progress tool to assist human creativity; suggesting source domains has been made towards such a creative analogy model? to people, to enable them to re-interpret a given target What are the main challenges that lie ahead? problem. Finally, it could be used as one possible model of In this paper we envisage a creative process that can take how people analogize in a creative means. any given target description and using a pre-stored collec- The paper is structured as follows: first we describe the tion of domain descriptions, identify potentially creative 1 Kilaza model for generating creative analogies, briefly source domains with which to re-interpret the given prob- illustrating its operation on the famous atom:solar-system lem. This paper explores and evaluates the potential for a model of analogy to act as a creativity engine. 1 Kilaza is not an acronym. International Conference on Computational Creativity 2012 17 analogy. Then we present results that reflect the model’s are returned. It was intended that this diversity might ad- ability to re-generate some well-known h-creative analo- dress the quality of novelty (Ritchie, 2001) associated with gies (Boden, 1992). Finally, the implications of these re- creativity, retrieving more “unexpected” and potentially sults are assessed and some remaining challenges are dis- creative sources. Finally, our model of the validation phase cussed. attempts to filter out invalid inferences, addressing the quality (Ritchie, 2001) factor associated with computa- Analogy as an Engine of Creativity tional creativity. An analogy is a conceptual comparison between two col- Ritchie (2001) identifies the essential properties of crea- lections of concepts, a source and target (Gentner, 1983), tivity as being directed, novel and useful. We argue that such that the source highlights particular aspects of the our model is directed in that it focuses on re-interpreting target, possibly suggesting some new inferences about it. some given target domain. Our model addresses the nov- In creative analogies, an productive source domain con- elty property by its ability to retrieve potentially useful but jures up a new and revolutionary interpretations of the tar- semantically distant, even disconnected, source domains. get domain, triggering novel inferences that help explain Finally, the useful property is addressed through a valida- some previously incongruous phenomena or that help inte- tion process that imposes a quality measure on the infer- grate some seemingly unrelated phenomena (Boden, 1992; ences that are accepted by the model. Eysenck and Keane, 1995). Creative analogies differ from “ordinary” analogies primarily in the conceptual “distance” retrieval mapping validation between the source and target domains (i.e., these two do- mains may never have been linked before) and the useful- Figure 1: Kilaza is a three-phase model of Analogy ness of the resulting comparison. Both creative and mun- dane analogies appear to use the same analogical reasoning process, as described in the following section, but different Analogical Retrieval Phase-Model in their inputs and outputs. Existing models for analogical retrieval suffer from the Kekulé’s is famous for his analogy between the carbon- limitations in the range of possible retrievals because their chain and a snake biting its own tail. But this analogy they either (i) focus exclusively on domain semantics (like could have been triggered by many alternative and more MAC/FAC; Forbus, Gentner and Law, 1995) or (ii) focus mundane source domains – from tying his own shoe-lace primarily on domain semantics (like HRR; Plate, 1998). to buckling his belt. While many source domains could Other models -- such as ARCS (Thagard et al, 1990) and have generated the creative carbon-ring structure, Gick and Rebuilder (Gomes et al, 2006) - supplement domain repre- Holyoak (1980) have shown most people (including Ke- sentations by elaboration from external sources (like kulé) frequently fail to notice many potential analogies. WordNet) to widen the net to include more semantically This highlights one potential advantage of a computational non-identical sources. However, all of these approaches model, in that a model can tirelessly explore all potential arguably over-constraint retrieval for the the proposes of analogies, returning only the most promising comparisons creativity. We argue that a creative retrieval process must to a user for more detailed consideration. Thus, computa- allow semantically distant and even semantically discon- tional models could potentially act a tools helping people nected sources to be retrieved, ideally without overwhelm- overcome one barrier; namely, their failure to perceive ing the subsequent phase-models with irrelevant domains. analogies when they are present. liz liz Kilaza Analogical Creativity Engine loves loves loves Keane (1994) presented a five-phase model of the analogi- loves cal reasoning process, which recognises the distinct phases tom jo tom jo loves loves of representation, retrieval, mapping, validation and in- duction. While other authors describe slightly different (a) Love Triangle (b) Unrequited Love subdivisions of this process, there is broad agreement on these phases. Our computational model encompasses the Figure 2: Topology is a key characteristic in retrieving creative three central phases of analogy (see Figure 1). We high- source domains light that Walls & Hadamard subdivide creativity into the phases of preparation, incubation, illumination and verifi- Gentner
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