Naturalism and wonder: Peirce on the logic of Hume’s argument against miracles

How should we proceed when confronted with a phenomenon (or evidence which points towards a phenomenon) which baffles us? The term "miracle" is a convenient term on which to hang this question. It has a religious meaning, and the arguments I will be discussing are applicable to the case of deciding, for example, whether to believe in the Judaeo-Christian God, based on the reports of miracles offered by the Bible. However, one can generalise from this case to deeper issues about our attitude to the apparently inexplicable. By the apparently inexplicable I mean that which contradicts our most well-confirmed beliefs. This general question is the theme of this paper

Modernity and morality in Habermas's discourse ethics

Discourse ethics is originally conceived as a programme of philosophical justification of morality. This depends on the formal derivation of the moral principle (U) from non-moral principles. The moral theory is supposed to fall out of a pragmatic theory of meaning. The original programme plays a central role in Habermas's social theory: the moral theory, if true, provides good evidence for the more general theory of modernization. But neither Habermas nor his followers have succeeded in providing a formal derivation. This essay shows how and why Habermas's proposed derivation is impossible. As if aware of the lacuna, Habermas has recently suggested that (U) can be derived by 'abduction' rather than deduction. The proposal draws heavily on modernization theory; hence the only justification for (U) now available to him rests on premises drawn from that theory. The original programme of the justification of morality has thus given way to the weaker programme of the philosophical elucidation of morality. Further, since Habermas's moral theory is no longer justified independently of modernization theory, but at least partly by it, the moral theory cannot without circularity provide evidence for the modernization theory

A comparative survey of integrated learning systems

This paper presents the duction framework for unifying the three basic forms of inference - deduction, abduction, and induction - by specifying the possible relationships and influences among them in the context of integrated learning. Special assumptive forms of inference are defined that extend the use of these inference methods, and the properties of these forms are explored. A comparison to a related inference-based learning frame work is made. Finally several existing integrated learning programs are examined in the perspective of the duction framework

Інтегрований підхід до поєднання невизначеностей з використанням функцій довіри

Стаття присвячена теоретичним аспектам обгрунтування рішень при наявності конкуруючих гіпотез. В контексті задач дослідження розглянуті особливості прийняття рішень з використанням структур довіри. Виділена проблема конфліктів, яка є невирішуваною в класичній моделі. Удосконалена модель прийняття рішень шляхом використання додаткової процедури їх комбінування

Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings

Despite the great success of neural visual generative models in recent years, integrating them with strong symbolic knowledge reasoning systems remains a challenging task. The main challenges are two-fold: one is symbol assignment, i.e. bonding latent factors of neural visual generators with meaningful symbols from knowledge reasoning systems. Another is rule learning, i.e. learning new rules, which govern the generative process of the data, to augment the knowledge reasoning systems. To deal with these symbol grounding problems, we propose a neural-symbolic learning approach, Abductive Visual Generation (AbdGen), for integrating logic programming systems with neural visual generative models based on the abductive learning framework. To achieve reliable and efficient symbol assignment, the quantized abduction method is introduced for generating abduction proposals by the nearest-neighbor lookups within semantic codebooks. To achieve precise rule learning, the contrastive meta-abduction method is proposed to eliminate wrong rules with positive cases and avoid less-informative rules with negative cases simultaneously. Experimental results on various benchmark datasets show that compared to the baselines, AbdGen requires significantly fewer instance-level labeling information for symbol assignment. Furthermore, our approach can effectively learn underlying logical generative rules from data, which is out of the capability of existing approaches

Three Pragmatist Legacies in the Thought of Umberto Eco

Pragmatism was one of the greatest influences on Umberto Eco\u2019s intellectual adventure. In this paper, I will try to identify three large legacies of pragmatism which were central in Eco\u2019s thought and which shaped and influenced his philosophy to its foundations. The three of Eco\u2019s overarching ideas that are marked in their very essence by pragmatic legacy are: i) the non-separation of semantics and pragmatics; ii) the centrality of abduction for cognition and semiotic thought; iii) synechism, or rather, the continuity between mind and world that Eco was unwilling to allow on a theoretical level, but which he explicitly puts on stage in narration

Towards a Science of Life as Creative Organisms

Life here means the organizing principles that are creating all forms of life. And all forms of life are organisms and they obey universals.nbsp; These principles obey very different kinds of logic than that known in scientific materialism of physics.nbsp; To understand life, a new foundation of metaphysics with matching logic is required. Towards that end I bring into question scientific materialism and advance considerations for the foundations of a new science for life in which life and values are fundamental and life is creative organisms

An automated reasoning framework for translational research

AbstractIn this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools.In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results