Lorenzo Magnani

Abduction, reason, and science : processes of discovery and explanation

1. Hypothesis Generation. 2. Theoretical Abduction. 3. Manipulative abduction. 4. Diagnostic Reasoning. 5. Visual, Temporal Abduction. 6. Governing inconsistencies. 7. Hypothesis Withdrawal in Science. References. Author Index. Subject Index.

An epistemological framework for medical knowledge-based systems

An abstraction paradigm for unifying different perspectives concerning the analysis and design of knowledge-based systems (KBSs) is presented. The model accounts for all of the conceptual features of knowledge-based systems, thus making clear which features are intrinsic to the problem and which are artifacts of the implementation. The proposal is based on a two-level analysis of knowledge-based systems: an epistemological and a computational level. At the first level, ontology and inference models of a knowledge-based system are defined. At the computational level, methods and formalisms are adopted after the epistemological analysis has been carried out. The study is confined to medicine with three generic tasks identified: diagnosis, therapy planning, and monitoring. The results of this analysis indicate that the generic tasks manage different ontologies, but can be executed exploiting a unique inference model. Computational issues are discussed to argue that the model provides a conceptual view on existing systems and some design insights for future ones. >

Morality in a Technological World: Knowledge as Duty

1. Respecting people as things 2. Treating people as means 3. Hybrid people, hybrid selves 4. Knowledge as duty 5. Freedom and responsibility 6. Creating ethics 7. Inferring reasons.

MODEL-BASED REASONING IN SCIENCE AND TECHNOLOGY

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Epistemic Mediators and Model-Based Discovery in Science

What I call theoretical abduction (sentential and model-based) certainly illustrates much of what is important in abductive reasoning, especially the objective of selecting and creating a set of hypotheses that are able to dispense good (preferred) explanations of data, but fails to account for many cases of explanations occurring in science or in everyday reasoning when the exploitation of the environment is crucial. The concept of manipulative abduction is devoted to capture the role of action and of external representations in many interesting situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. I will present some aspects of this kind of reasoning derived from the “cognitive” history of the discovery of the non-Euclidean geometries. Geometrical diagrams are considered external representations which play both a mirror role (to externalize rough mental models), and an unveiling role (as gateways to imaginary entities). I describe them as epistemic mediators able to perform various abductive tasks (discovery of new properties or new propositions/hypotheses, provision of suitable sequences of models as able to convincingly verifying theorems, etc.).

Model-Based Creative Abduction

My contribution aims to introduce the distinction, not previously analyzed, between two kinds of abduction,theoretical and manipulative, in order to provide an integrated framework to explain some of the main aspects of both creative and model-based reasoning effects engendered by the practice of science. The distinction appears to be extremely convenient: creativity will be viewed as the result of the highest cases of theoretical abduction showing the role of the so-called model-based abduction. Moreover, I will delineate the first features of what I call manipulative abduction showing how we can find methods of constructivity at the experimental stage, where the recent epistemological tradition has settled the most negative effects of theory-ladenness.

NEOANEMIA: a knowledge-based system emulating diagnostic reasoning

Medical diagnosis can be modeled in terms of the classical notions of abduction, deduction, and induction. Abduction is making a preliminary guess that allows one to establish a set of plausible diagnostic hypotheses, followed by deduction for exploring their consequences and induction for testing the hypotheses with available patient data or for planning the acquisition of new data. Such a description of diagnostic reasoning at a knowledge level helps the construction of an expert system by fashioning the adopted expert system building tool to reflect the structure of the problem rather than by fitting the problem to the tool. To this aim, reasoning strategies need to be represented abstractly, separate from medical facts and relations, to make the design more transparent and explainable.

Model-Based Reasoning in Science, Technology, and Medicine

Abduction, Problem Solving, and Practical Reasoning.- Animal Abduction.- Communicative Gestures Facilitate Problem Solving for Both Communicators and Recipients.- The Concept of Fallacy is Empty.- Abductive Reasoning, Information, and Mechanical Systems.- Automated Abduction in Scientific Discovery.- Abduction, Medical Semeiotics and Semioethics.- Abduction and Modeling in Biosemiotics and Sociosemiotics.- Reason out Emergence from Cellular Automata Modeling.- Belief Ascription and De Re Communication.- Multiagent-Based Simulation in Biology.- Mathematics through Diagrams: Microscopes in Non-Standard and Smooth Analysis.- Models, Mental Models, Representations, and Medical Reasoning.- Cognition, Environment and the Collapse of Civilizations.- Cognitive Aspects of Tacit Knowledge and Cultural Diversity.- The Functional-Analogical Explanation in Chinese Science and Technology.- Model-Based Reasoning and Diagnosis in Traditional Chinese Medicine (TCM).- Model-Based Reasoning in Cognitive Science.- An Examination of Model-Based Reasoning in Science and Medicine in India.- Ontology, Artefacts, and Models of Reasoning.- The Wondering Angels of the Fractal Art.- Logical and Computational Aspects of Model-Based Reasoning.- Polynomizing: Logic Inference in Polynomial Format and the Legacy of Boole.- Abductive Inference and Iterated Conditionals.- Peircean Pragmatic Truth and da Costas Quasi-Truth.- Sliding Mode Motion Control Strategies for Rigid Robot Manipulators.- Model-Based Chemical Compound Formulation.- Model-Based Reasoning for Self-Repair of Autonomous Mobile Robots.- Application of Bayesian Inference to Automatic Semantic Annotation of Videos.- An Algebraic Approach to Model-Based Diagnosis.- CYBERNARD: A Computational Reconstruction of Claude Bernards Scientific Discoveries.- Do Computational Models of Reading Need a Bit of Semantics?.

Sharing Representations and Creating Chances through Cognitive Niche Construction. The Role of Affordances and Abduction

As a matter of fact, humans continuously delegate and distribute cognitive functions to the environment to lessen their limits. They build models, representations, and other various mediating structures, that are considered to aid thought. In doing these, humans are engaged in a process of cognitive niche construction. In this sense, we argue that a cognitive niche emerges from a network of continuous interplays between individuals and the environment, in which people alter and modify the environment by mimetically externalizing fleeting thoughts, private ideas, etc., into external supports. For cognitive niche construction may also contribute to make available a great portion of knowledge that otherwise would remain simply unexpressed or unreachable. This can turn to be useful especially for all those situations that require to transmit and share knowledge, information, and, more generally, cognitive resources. In dealing with the exploitation of cognitive resources embedded in the environment, the notion of affordance, originally proposed by Gibson [1] to illustrate the hybrid character of visual perception, together with the proximal/distal distinction described by Brunswik [2], are extremely relevant. In order to solve various controversies on the concept of affordance and on the status of the proximal/distal dichotomy, we will take advantage of some useful insights that come from the study on abduction. Abduction may also fruitfully describe all those human and animal hypothetical inferences that are operated through actions which consist in smart manipulations to both detect new affordances and to create manufactured external objects that offer new affordances/cues.

Is abduction ignorance-preserving? Conventions, models and fictions in science

Abduction is a procedure in which something that lacks classical explanatory epistemic virtue can be accepted because it has virtue of another kind: Gabbay and Woods (2005, The Reach of Abduction) contend (GW-model) that abduction presents an ignorance-preserving or (ignorance-mitigating) character. From this perspective abductive reasoning is a response to an ignorance-problem; through abduction the basic ignorance—that does not have to be considered a total ‘ignorance’—is neither solved nor left intact. Abductive reasoning is an ignorance-preserving accommodation of the problem at hand. Is abduction really ignorance-preserving? To better answer this question I will take advantage of my eco-cognitive model (EC-model) of abduction and of three examples taken from the areas of both philosophy and epistemology. It will be illustrated that through abduction, knowledge can be enhanced, even when abduction is not considered an inference to the best explanation (IBE) in the classical sense of the expression, i.e. an inference necessarily characterized by an empirical evaluation phase, or an inductive phase, as Peirce called it. (1) Peirce provides various justifications of the knowledge enhancing role of abduction, even when abduction is not considered an IBE in the classical sense of the expression, i.e. an inference necessarily characterized by an empirical evaluation phase, or inductive phase. These justifications basically resort to the conceptual exploitation of evolutionary and metaphysical ideas, which clearly show that abduction is constitutively akin to truth, even if certainly always ignorance-preserving or mitigating in the sense that the ‘absolute truth’ is never reached through abduction; (2) in empirical science abducing conventions favours and increases knowledge even if these hypotheses remain evidentially inert—at least in the sense that it is not possible to empirically falsify them. Consequently abduced conventions are evidentially inert but knowledge enhancing at the rational level of science; (3) in science we do not have to confuse the process of abducing models with the process of abducing fictions: the recent epistemological conundrum concerning fictionalism presents to us the epistemic situation in which the models abduced by scientists reveal themselves not to be ‘airy nothings’ at all, and certainly different in their gnoseological status from literary fictions. Scientific models instead play fundamental ‘rational’ knowledge enhancing roles: in a static perspective (e.g. when inserted in a textbook) scientific models can appear fictional to the epistemologist, but their fictional character disappears if a dynamic perspective is adopted. Abduction in scientific model-based reasoning is not a suspicious process of guessing fictions.