Abductive Reasoning,Interpretation and Collaborative Processes

In this paper we want to examine how the mutual understanding of speakers is reached during a conversation through collaborative processes, and what role is played by abductive inference (in the Peircean sense) in these processes. We do this by bringing together contributions coming from a variety of disciplines, such as logic, philosophy of language and psychology. When speakers are engaged in a conversation, they refer to a supposed common ground: every participant ascribes to the others some knowledge, belief, opinion etc. on which to rely in order to reach mutual understanding. As the conversation unfolds, this common ground is continually corrected and reshaped by the interchanges. An abductive reasoning takes place, in a collaborative setting, in order to build new possible theories about the common ground. In reconstructing this process through the use of a working example, we argue that the integration of a collaborative perspective within the Peircean theory of abduction can help to solve some of the drawbacks that the critics of the latter have outlined, for example its permissivity and non generativity.

Schwinger and the Ontology of Quantum Field Theory

An epistemological interpretation of quantum mechanics hinges on the claim that the distinctive features of quantum mechanics can be derived from some distinctive features of an observational basis. Old and new variations of this theme are listed. The program has a limited success in non-relativistic quantum mechanics. The crucial issue is how far it can be extended to quantum field theory without introducing significant ontological postulates. A C*-formulation covers algebraic quantum field theory, but not the standard model. Julian Schwinger’s anabatic methodology extended a strict measurement-based formulation of quantum mechanics through field theory. His extension also excluded the quark hypothesis and the standard model. Quarks and local gauge invariance are postulates that go beyond the limits of an epistemological interpretation of quantum mechanics. The ontological significance ascribed to these advances depends on the role accorded ontology.

Seeking Allies: Modelling How Listeners Choose Their Musical Friends

In this paper we describe in some detail a formal computer model of inferential discourse based on a belief system. The key issue is that a logical model in a computer, based on rational sets, can usefully model a human situation based on irrational sets. The background of this work is explained elsewhere, as is the issue of rational and irrational sets (Billinge and Addis, in: Magnani and Dossena (eds.), Computing, philosophy and cognition, 2004; Stepney et al., Journey: Non-classical philosophy—socially sensitive computing in journeys non-classical computation: A grand challenge for computing research, 2004). The model is based on the Belief System (Addis and Gooding, Proceedings of the AISB’99 Symposium on Scientific Creativity, 1999) and it provides a mechanism for choosing queries based on a range of belief. We explain how it provides a way to update the belief based on query results, thus modelling others’ experience by inference. We also demonstrate that for the same internal experience, different models can be built for different actors.

Conceptual Barriers to Progress Within Evolutionary Biology

In spite of its success, Neo-Darwinism is faced with major conceptual barriers to further progress, deriving directly from its metaphysical foundations. Most importantly, neo-Darwinism fails to recognize a fundamental cause of evolutionary change, “niche construction”. This failure restricts the generality of evolutionary theory, and introduces inaccuracies. It also hinders the integration of evolutionary biology with neighbouring disciplines, including ecosystem ecology, developmental biology, and the human sciences. Ecology is forced to become a divided discipline, developmental biology is stubbornly difficult to reconcile with evolutionary theory, and the majority of biologists and social scientists are still unhappy with evolutionary accounts of human behaviour. The incorporation of niche construction as both a cause and a product of evolution removes these disciplinary boundaries while greatly generalizing the explanatory power of evolutionary theory.

Distributed Morality: Externalizing Ethical Knowledge in Technological Artifacts

Technology moves us to a better world. We contend that through technology people can simplify and solve moral tasks when they are in presence of incomplete information and possess a diminished capacity to act morally. Many external things, usually inert from the moral point of view, can be transformed into the so-called moral mediators. Hence, not all of the moral tools are inside the head, many of them are shared and distributed in “external” objects and structures which function as ethical devices.

Simulation Methods for an Abductive System in Science

We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of ‘belief’ as the propensity to choose a particular course of action.

Trading Zones,Moral Imagination and Socially Sensitive Computing

As computating technologies become ubiquitous and at least partly autonomous, they will have increasing impact on societies, both in the developed and developing worlds. This article outlines a framework for guiding emerging technologies in directions that promise social as well as technical progress. Multiple stakeholders will have to be engaged in dialogues over new technological directions, forming trading zones in which knowledge and resources are exchanged. Such discussions will have to incorporate cultural and individual values.

Nonlinear Cobweb of Cognition

The modern conception of enactive cognition is under discussion from the standpoint concerning the notions of nonlinear dynamics and synergetics. The contribution of Francisco Varela and his precursors is considered. It is shown that the perceptual and mental processes are bound up with the “architecture” of human body and nonlinear and circular connecting links between the subject of cognition and the world constructed by him can be metaphorically called a nonlinear cobweb of cognition. Cognition is an autopoietic activity because it is directed to the search of elements that are missed; it serves to completing integral structures.

Modelling Experiments as Mediating Models

Syntactic and structural models specify relationships between their constituents but cannot show what outcomes their interaction would produce over time in the world. Simulation consists in iterating the states of a model, so as to produce behaviour over a period of simulated time. Iteration enables us to trace the implications and outcomes of inference rules and other assumptions implemented in the models that make up a theory. We apply this method to experiments which we treat as models of the particular aspects of reality they are designed to investigate. Scientific experiments are constantly designed and re-designed in the context of implementation and use. They mediate between theoretical understanding and the practicalities of engaging with the empirical and social world. In order to model experiments we need to identify and represent features that all experiments have in common. We treat these features as parameters of a general model of experiment so that by varying these parameters different types of experiment can be modelled.

A Framework Linking Non-Living and Living Systems: Classification of Persistence, Survival and Evolution Transitions

We propose a framework for analyzing the development, operation and failure to survive of all things, living, non-living or organized groupings. This framework is a sequence of developments that improve survival capability. Framework processes range from origination of any entity/system, to the development of increased survival capability and development of life-forms and organizations that use intelligence. This work deals with a series of developmental changes that arise from the uncovering of emergent properties. The framework is intended to be general, but we see a potential to apply it to scientific topics such as the exploration of the origin of life or the search for life beyond Earth, and to understand some biological issues in evolution and symbiosis, and also to apply to social systems that do not seem to be operating well, to determine their problems and correct them.

The Foundationalism–Coherentism Opposition Revisited: The Case for Complementarism

In this paper, I show the complementarity of foundationalism and coherentism with respect to any efficient system of beliefs by means of a distinction between two types of proposition drawn from an analogy with an axiomatic system. This distinction is based on the way a given proposition is acknowledged as true, either by declaration (F-proposition) or by preservation (C-proposition). Within such a perspective, i.e., epistemological complementarism, not only can one see how the usual opposition between foundationalism and coherentism is irrelevant, but furthermore one can appreciate the reciprocal relation between these two theories as they refer to two separate epistemological functions involved in the dynamics of constituting and expanding an epistemic system.

The Constructive Realist Account of Science and Its Application to Ilya Prigogine’s Conception of Laws of Nature

Sciences are often regarded as providing the best, or, ideally, exact, knowledge of the world, especially in providing laws of nature. Ilya Prigogine, who was awarded the Nobel Prize for his theory of non-equilibrium chemical processes—this being also an important attempt to bridge the gap between exact and non-exact sciences [mentioned in the Presentation Speech by Professor Stig Claesson (nobelprize.org, The Nobel Prize in Chemistry 1977)]—has had this ideal in mind when trying to formulate a new kind of science. Philosophers of science distinguish theory and reality, examining relations between these two. Nancy Cartwright’s distinction of fundamental and phenomenological laws, Rein Vihalemm’s conception of the peculiarity of the exact sciences, and Ronald Giere’s account of models in science and science as a set of models are deployed in this article to criticise the common view of science and analyse Ilya Prigogine’s view in particular. We will conclude that on a more abstract, philosophical level, Prigogine’s understanding of science doesn’t differ from the common understanding.

Using Wittgenstein’s Family Resemblance Principle to Learn Exemplars

The introduction of the notion of family resemblance represented a major shift in Wittgenstein’s thoughts on the meaning of words, moving away from a belief that words were well defined, to a view that words denoted less well defined categories of meaning. This paper presents the use of the notion of family resemblance in the area of machine learning as an example of the benefits that can accrue from adopting the kind of paradigm shift taken by Wittgenstein. The paper presents a model capable of learning exemplars using the principle of family resemblance and adopting Bayesian networks for a representation of exemplars. An empirical evaluation is presented on three data sets and shows promising results that suggest that previous assumptions about the way we categories need reopening.

A Multiagent Approach to Modelling Complex Phenomena

Designing models of complex phenomena is a difficult task in engineering that can be tackled by composing a number of partial models to produce a global model of the phenomena. We propose to embed the partial models in software agents and to implement their composition as a cooperative negotiation between the agents. The resulting multiagent system provides a global model of a phenomenon. We applied this approach in modelling two complex physiological processes: the heart rate regulation and the glucose-insulin metabolism. Beyond the effectiveness demonstrated in these two applications, the idea of using models associated to software agents to give reason of complex phenomena is in accordance with current tendencies in epistemology, where it is evident an increasing use of computational models for scientific explanation and analysis. Therefore, our approach has not only a practical, but also a theoretical significance: agents embedding models are a technology suitable both to representing and to investigating reality.

Steps from Erratic Projects towards Structured Programs in Research

Currently, research is mostly organized in research projects intended to provide results within a limited period of time. Here, small teams of scientists erratically define single scientific studies, write a proposal, and send it to the refereeing board. In case of a funding, the study is carried out and the results are published. To optimize the research and reduce the respective costs and/or raise the outcome, multiple research projects should be organized within a comprehensive research program. A meta-model (paradigm) can help comprise (a) the representation of the state-of-the-art decision knowledge, (b) the adding of new research questions, (c) the performing of trials to answer these questions, and (d) the revision of the current model. It will be discussed how to structure studies within research programs and these within one super-program.

The Emergence of Symbolic Algebra as a Shift in Predominant Models

Historians of science find it difficult to pinpoint to an exact period in which symbolic algebra came into existence. This can be explained partly because the historical process leading to this breakthrough in mathematics has been a complex and diffuse one. On the other hand, it might also be the case that in the early twentieth century, historians of mathematics over emphasized the achievements in algebraic procedures and underestimated the conceptual changes leading to symbolic algebra. This paper attempts to provide a more precise setting for the historical context in which this decisive step to symbolic reasoning took place. For that purpose we will consider algebraic problem solving as model-based reasoning and symbolic representation as a model. This allows us to characterize the emergence of symbolic algebra as a shift from a geometrical to a symbolic mode of representation. The use of the symbolic as a model will be situated in the context of mercantilism where merchant activity of exchange has led to reciprocal relations between money and wealth.

The Differential Method and the Causal Incompleteness of Programming Theory in Molecular Biology

The “DNA is a program” metaphor is still widely used in Molecular Biology and its popularization. There are good historical reasons for the use of such a metaphor or theoretical model. Yet we argue that both the metaphor and the model are essentially inadequate also from the point of view of Physics and Computer Science. Relevant work has already been done, in Biology, criticizing the programming paradigm. We will refer to empirical evidence and theoretical writings in Biology, although our arguments will be mostly based on a comparison with the use of differential methods (in Molecular Biology: a mutation or alike is observed or induced and its phenotypic consequences are observed) as applied in Computer Science and in Physics, where this fundamental tool for empirical investigation originated and acquired a well-justified status. In particular, as we will argue, the programming paradigm is not theoretically sound as a causal(as in Physics) or deductive(as in Programming) framework for relating the genome to the phenotype, in contrast to the physicalist and computational grounds that this paradigm claims to propose.

Embodied Anomaly Resolution in Molecular Genetics: A Case Study of RNAi

Scientific anomalies are observations and facts that contradict current scientific theories and they are instrumental in scientific theory change. Philosophers of science have approached scientific theory change from different perspectives as Darden (Theory change in science: Strategies from Mendelian genetics, 1991) observes: Lakatos (In: Lakatos, Musgrave (eds) Criticism and the growth of knowledge, 1970) approaches it as a progressive “research programmes” consisting of incremental improvements (“monster barring” in Lakatos, Proofs and refutations: The logic of mathematical discovery, 1976), Kuhn (The structure of scientific revolutions, 1996) observes that changes in “paradigms” are instigated by a crisis from some anomaly, and Hanson (In: Feigl, Maxwell (eds) Current issues in the philosophy of science, 1961) proposes that discovery does not begin with hypothesis but with some “problematic phenomena requiring explanation”. Even though anomalies are important in all of these approaches to scientific theory change, there have been only few investigations into the specific role anomalies play in scientific theory change. Furthermore, much of these approaches focus on the theories themselves and not on how the scientists and their experiments bring about scientific change (Gooding, Experiment and the making of meaning: Human agency in scientific observation and experiment, 1990). To address these issues, this paper approaches scientific anomaly resolution from a meaning construction point of view. Conceptual integration theory (Fauconnier and Turner, Cogn Sci 22:133–187, 1996; The way we think: Conceptual blending and mind’s hidden complexities, 2002) from cognitive linguistics describes how one constructs meaning from various stimuli, such as text and diagrams, through conceptual integration or blending. The conceptual integration networks that describe the conceptual integration process characterize cognition that occurs unconsciously during meaning construction. These same networks are used to describe some of the cognition while resolving an anomaly in molecular genetics called RNA interference (RNAi) in a case study. The RNAi case study is a cognitive-historical reconstruction (Nersessian, In: Giere (ed) Cognitive models of science, 1992) that reconstructs how the RNAi anomaly was resolved. This reconstruction traces four relevant molecular genetics publications in describing the cognition necessary in accounting for how RNAi was resolved through strategies (Darden 1991), abductive reasoning (Peirce, In: Hartshorne, Weiss (eds) Collected papers, 1958), and experimental reasoning (Gooding 1990). The results of the case study show that experiments play a crucial role in formulating an explanation of the RNAi anomaly and the integration networks describe the experiments’ role. Furthermore, these results suggest that RNAi anomaly resolution is embodied. It is embodied in a sense that cognition described in the cognitive-historical reconstruction is experientially based.

Inventing Electric Potential

Investigations with electrometers in the 1770s led Volta to envision mobile charge in electrical conductors as a compressible fluid. A pressure-like condition in this fluid, which Volta described as the fluid’s “effort to push itself out” of its conducting container, was the causal agent that makes the fluid move. In this paper I discuss Volta’s use of analogy and imagery in model building, and compare with a successful contemporary conceptual approach to introducing ideas about electric potential in instruction. The concept that today is called “electric potential” was defined mathematically by Poisson in 1811. It was understood after about 1850 to predict the same results in conducting matter as Volta’s pressure-like concept—and to predict electrostatic effects in the exterior space where Volta’s concept had nothing to say. Complete quantification in addition to greater generality made the mathematical concept a superior research tool for scientists. However, its spreading use in instruction has marginalized approaches to model building based on the analogy and imagery resources that students bring into the classroom. Data from pre and post testing in high schools show greater conceptual and confidence gains using the new conceptual approach than using conventional instruction. This provides evidence for reviving Volta’s compressible fluid model as an intuitive foundation which can then be modified to include electrostatic distant action. Volta tried to modify his compressible fluid model to include distant action, using imagery borrowed from distant heating by a flame. This project remained incomplete, because he did not envision an external field mediating the heating. However, pursuing Volta’s strategy of model modification to completion now enables students taught with the new conceptual approach to add distant action to an initial compressible fluid model. I suggest that a partial correspondence to the evolving model sequence that works for beginning students can help illuminate Volta’s use of intermediate explanatory models.