Modelling Scientific Discovery

Traditionally, the Philosophy of Science has examined the nature of scientific discovery. In recent years, Cognitive Science has gathered together work in Artificial Intelligence (AI) and Cognitive Psychology that attempts to understand scientific discovery. However, at present, there is no generally accepted account of scientific discovery in any of these disciplines. This thesis aims further to explore the nature of scientific discovery from an AI perspective, but does so within a clearly defined Framework, designed to structure cognitive science research on scientific discovery. The framework proposes a minimum set of components as a guide to the construction of acceptable accounts of scientific discovery. The focal concept is the Research Programme; a body of research that investigates a delimited set of phenomena using a Theoretical component and an Experimental component. The framework posits: three types of theoretical knowledge; three levels of experiments; inferences to apply and generate new theoretical & experimental knowledge; criteria for assessing the acceptability of theories & the reliability of experiments; and multiple levels of communication between the components. Previous computer models and empirical studies of scientific discovery are reviewed. They tend not to offer complete accounts of scientific discovery, as defined by the framework. In particular, many completely ignore the crucial role of experiments. The STERN computational model of scientific discovery is introduced. It instantiates all the components of the Framework. STERN currently models discoveries made by Galileo in the domain of naturally accelerated terrestrial motion, although it may be applied more generally. STERN has four main strategies that are used to make discoveries: (i) confirming existing hypotheses; (ii) generalizing experimental results to form new hypotheses; (iii) generating new hypotheses from known hypotheses; and (iv) generating new experiments. STERN is more complete than previous computational models. As such it allows novel heuristics at the level of research programmes to be investigated and high level abilities to emerge from its complexity

Conceptual Modelling, Combinatorial Heuristics and Ars Inveniendi: An Epistemological History

(1) An introduction to the principles of conceptual modelling, combinatorial heuristics and epistemological history; (2) the examination of a number of perennial epistemological-methodological schemata: conceptual spaces and blending theory; ars inveniendi and ars demonstrandi; the two modes of analysis and synthesis and their relationship to ars inveniendi; taxonomies and typologies as two fundamental epistemic structures; extended cognition, symbolic systems and model-based reasoning

Technology and/as Theory: Material Thinking in Ancient Science and Medicine

Multiple natural philosophers in antiquity proposed that nature possessed considerable technical skill. Yet, the specific conceptual implications of this assertion were quite different in fourth century BCE Athens--with its pots, bronze tools and cisterns--than in second century CE Rome--where large-scale aqueducts, elaborate water machines and extensive glassworks were commonplace. This dissertation assesses the impact that these different technological environments had on philosophical and scientific theories. In short, it argues that contemporary technologies shaped ancient philosophers' physical assumptions by providing cognitive tools with which to understand natural phenomena. As a result, as technologies evolved--even in relatively modest ways--so too did conceptual models of the natural world. To explore these assertions, this dissertation focuses on two main fields of explanation, the vascular system and vision, and includes investigations of such technologies as pipes, pumps, mirrors, wax tablets, diagrams and experimental apparatuses. It demonstrates the ways in which scientific theorists use the specific material technologies around them as heuristics to conceptualize physical processes

How Philosophy of Mind Needs Philosophy of Chemistry

By the 1960s many (perhaps most) philosophers had adopted ‘physicalism’ ─ the view that physical causes fully account for mental activities. However, controversy persists about what count as ‘physical causes’. ‘Reductive’ physicalists recognize only microphysical (elementary-particle-level) causality. Many (perhaps most) physicalists are ‘non-reductive’ ─ they hold that entities considered by other (‘special’) sciences have causal powers. Philosophy of chemistry can help resolve main issues in philosophy of mind in three ways: developing an extended mereology applicable to chemical combination, testing whether ‘singularities’ prevent reduction of chemistry to microphysics, and demonstrating ‘downward causation’ in complex networks of chemical reactions

How Philosophy of Mind Needs Philosophy of Chemistry

By the 1960s many (perhaps most) philosophers had adopted ‘physicalism’ ─ the view that physical causes fully account for mental activities. However, controversy persists about what count as ‘physical causes’. ‘Reductive’ physicalists recognize only microphysical (elementary-particle-level) causality. Many (perhaps most) physicalists are ‘non-reductive’ ─ they hold that entities considered by other (‘special’) sciences have causal powers. Philosophy of chemistry can help resolve main issues in philosophy of mind in three ways: developing an extended mereology applicable to chemical combination, testing whether ‘singularities’ prevent reduction of chemistry to microphysics, and demonstrating ‘downward causation’ in complex networks of chemical reactions

Player agency in interactive narrative: audience, actor & author

The question motivating this review paper is, how can computer-based interactive narrative be used as a constructivist learn- ing activity? The paper proposes that player agency can be used to link interactive narrative to learner agency in constructivist theory, and to classify approaches to interactive narrative. The traditional question driving research in interactive narrative is, ‘how can an in- teractive narrative deal with a high degree of player agency, while maintaining a coherent and well-formed narrative?’ This question derives from an Aristotelian approach to interactive narrative that, as the question shows, is inherently antagonistic to player agency. Within this approach, player agency must be restricted and manip- ulated to maintain the narrative. Two alternative approaches based on Brecht’s Epic Theatre and Boal’s Theatre of the Oppressed are reviewed. If a Boalian approach to interactive narrative is taken the conflict between narrative and player agency dissolves. The question that emerges from this approach is quite different from the traditional question above, and presents a more useful approach to applying in- teractive narrative as a constructivist learning activity

The emergence of scientific understanding in current ecological research practice

Scientific understanding as a subject of inquiry has become widely discussed in philosophy of science and is often addressed through case studies from history of science. Even though these historical reconstructions engage with details of scientific practice, they usually provide only limited information about the gradual formation of understanding in ongoing processes of model and theory construction. Based on a qualitative ethnographic study of an ecological research project, this article shifts attention from understanding in the context of historical case studies to evidence of current case studies. By taking de Regt's (2017) contextual theory of scientific understanding into the field, it confirms core tenets of the contextual theory (e.g. the crucial role of visualization and visualizability) suggesting a normative character with respect to scientific activities. However, the case study also shows the limitations of de Regt's latest version of this theory as an attempt to explain the development of understanding in current practice. This article provides a model representing the emergence of scientific understanding that exposes main features of scientific understanding such as its gradual formation, its relation to skills and imagination, and its capacity for knowledge selectivity. The ethnographic evidence presented here supports the claim that something unique can be learned by looking into ongoing research practices that can’t be gained by studying historical case studies

Conceptual Modelling, Combinatorial Heuristics and Ars Inveniendi: An Epistemological History (Ch 1 & 2)

(1) An introduction to the principles of conceptual modelling, combinatorial heuristics and epistemological history; (2) the examination of a number of perennial epistemological-methodological schemata: conceptual spaces and blending theory; ars inveniendi and ars demonstrandi; the two modes of analysis and synthesis and their relationship to ars inveniendi; taxonomies and typologies as two fundamental epistemic structures; extended cognition, cognitio symbolica and model-based reasoning; (3) Plato’s notions of conceptual spaces, conceptual blending and hypothetical-analogical models (paradeigmata); (4) Ramon Llull’s concept analysis and combinatoric spaces; (5) Gottfried Leibniz’s development of compositional analysis and synthesis as a general modelling method and a paradigm for ars inveniendi; (6) Fritz Zwicky’s revival of the morphological method of analysis and construction, and its subsequent computerised applications

Composition heuristics and theories and a proposed heuristic for business writing

This work questions the usefulness of heuristic procedures, within composition in general writing in business in particular, as an effective aid to the generation of written, non-fiction discourse