Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used (...) to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data). (shrink)

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments (...) made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration. (shrink)

This book explores why, regarding practical reasoning, humans are sometimes still faster than artificial intelligence systems. It is the first to offer a self-contained presentation of neural network models for many computer science logics.

This paper studies methodologically robust options for giving logical contents to nodes in abstract argumentation networks. It defines a variety of notions of attack in terms of the logical contents of the nodes in a network. General properties of logics are refined both in the object level and in the metalevel to suit the needs of the application. The network-based system improves upon some of the attempts in the literature to define attacks in terms of defeasible proofs, the so-called rule-based (...) systems. We also provide a number of examples and consider a rigorous case study, which indicate that our system does not suffer from anomalies. We define consequence relations based on a notion of defeat, consider rationality postulates, and prove that one such consequence relation is consistent. (shrink)

The target article criticises neural-symbolic systems as inadequate for analogical reasoning and proposes a model of analogy as transformation (i.e., learning). We accept the importance of learning, but we argue that, instead of conflicting, integrated reasoning and learning would model analogy much more adequately. In this new perspective, modern neural-symbolic systems become the natural candidates for modelling analogy.

Humans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? -/- The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This (...) book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities. -/- The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems. (shrink)

This article aims to achieve two goals: to show that probability is not the only way of dealing with uncertainty ; and to provide evidence that logic-based methods can well support reasoning with uncertainty. For the latter claim, two paradigmatic examples are presented: logic programming with Kleene semantics for modelling reasoning from information in a discourse, to an interpretation of the state of affairs of the intended model, and a neural-symbolic implementation of input/output logic for dealing with uncertainty in dynamic (...) normative contexts. (shrink)

This book provides an invaluable overview of the reach of logic. It provides reference to some of the most important, well-established results in logic, while at the same time offering insight into the latest research issues in the area. It also has a balance of theory and practice, containing essays in the areas of modal logic, intuitionistic logic, logic and language, nonmonotonic logic and logic programming, temporal logic, logic and learning, combination of logics, practical reasoning, logic and artificial intelligence, abduction, (...) theorem proving and goal-directed reasoning. It will be invaluable reading for researchers and graduate students in logic and computer science, and a fabulous source of inspiration for research students in search of a topic for a PhD in logic and theoretical computer science. (shrink)

Abduction is or subsumes a process of inference. It entertains possible hypotheses and it chooses hypotheses for further scrutiny. There is a large literature on various aspects of non-symbolic, subconscious abduction. There is also a very active research community working on the symbolic (logical) characterisation of abduction, which typically treats it as a form of hypothetico-deductive reasoning. In this paper we start to bridge the gap between the symbolic and sub-symbolic approaches to abduction. We are interested in benefiting from developments (...) made by each community. In particular, we are interested in the ability of non-symbolic systems (neural networks) to learn from experience using efficient algorithms and to perform massively parallel computations of alternative abductive explanations. At the same time, we would like to benefit from the rigour and semantic clarity of symbolic logic. We present two approaches to dealing with abduction in neural networks. One of them uses Connectionist Modal Logic and a translation of Horn clauses into modal clauses to come up with a neural network ensemble that computes abductive explanations in a top-down fashion. The other combines neural-symbolic systems and abductive logic programming and proposes a neural architecture which performs a more systematic, bottom-up computation of alternative abductive explanations. Both approaches employ standard neural network architectures which are already known to be highly effective in practical learning applications. Differently from previous work in the area, our aim is to promote the integration of reasoning and learning in a way that the neural network provides the machinery for cognitive computation, inductive learning and hypothetical reasoning, while logic provides the rigour and explanation capability to the systems, facilitating the interaction with the outside world. Although it is left as future work to determine whether the structure of one of the proposed approaches is more amenable to learning than the other, we hope to have contributed to the development of the area by approaching it from the perspective of symbolic and sub-symbolic integration. (shrink)

En este breve comentario discuto algunos aspectos de la interpretación de la epistemología de Davidson que sugiere Willian Duica en su reciente libro. Luego de una presentación somera del libro me centro en tres asuntos centrales de la interpretación de Duica. En primer lugar, argumento que su lectura de la crítica de Davidson al dualismo esquema/contenido es muy restrictiva y deja abierta la posibilidad de un realismo directo empirista. En segundo lugar, argumento que en su lectura el propio Duica se (...) compromete inadvertidamente con un empirismo de este tipo y, de este modo, su interpretación entra en tensión con el coherentismo de Davidson. Finalmente, discuto algunos aspectos de la interpretación que hace Duica de la tesis davidsoniana de la triangulación. In this short comment I discuss some aspects of William Duica's interpretation of Davidson's epistemology in a recent book. After a brief review of the book, I focus on three central issues of Duica's interpretation. First, I argue that his reading of Davidson's criticism of the scheme/content dualism is too restrictive and leaves open the possibility of an empiricist direct realism. Second, I argue in his reading Duica inadvertently commits himself to an empiricism of this sort and, as a result, his interpretation is in tension with Davidson's own coherentism. Finally, I discuss some aspects of Duica's interpretation of Davidsonian triangulation. (shrink)

While there is significant consensus that undergraduate medical education should include bioethics training, there is widespread debate about how to teach bioethics to medical students. Educators disagree about course methods and approaches, the topics that should be covered, and the effectiveness and metrics for UME ethics training. One issue that has received scant attention is the timing of bioethics education during medical training. The existing literature suggests that most medical ethics education occurs in the pre-clinical years. Follow-up studies indicate that (...) medical students in their clinical rotations have little recall or ability to apply ethics concepts that were learned in their pre-clinical training. Trainees also report a desire for medical ethics to be taught in the context of practical application, which would suggest that the timing of pre-clinical ethics education is flawed. However, moving bioethics training to the clinical years should not be assumed to be the solution to the problems of recall and theory application. We argue that the effectiveness of timing bioethics education will depend on when medical students witness or experience particular categories of ethical dilemmas during their training. Our overarching hypothesis is that ethics education will be most effective when the bioethics training on a particular topic correlates to experiential exposure to that ethical issue. The purpose of our current study was to describe medical students exposure to particular categories of ethical conflicts, dilemmas, or issues. Our results may help bioethics educators better strategize about the most effective timing of medical ethics training in UME. (shrink)

Amyotrophic lateral sclerosis (ALS) is a progressive degenerative disorder of motor neurones. Although the genetic basis of familial forms of ALS has been well explored, the molecular basis of sporadic ALS is less well understood. Recent evidence has linked sporadic ALS with the failure to edit key residues in ionotropic glutamate receptors, resulting in excessive influx of calcium ions into motor neurones which in turn triggers cell death. Here we suggest that edited AMPA glutamate (GluR2) receptor subunits serve as gatekeepers (...) for motor neurone survival. BioEssays 30:1185–1192, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

The purpose of this study is to examine the relationship between the corporate social performance of an organization and three variables: the size of the organization, the financial performance of the organization, and the environmental performance of the organization. By empirically testing data from 1987 to 1992, the results of the study show that a firm's corporate social performance is indeed impacted by the size of the firm, the level of profitability of the firm, and the amount of pollution emissions (...) released by the firm. (shrink)

Ethical challenges surrounding the implementation of male circumcision as an HIV prevention strategyResearchers have been exploring the possibility of a correlation between male circumcision and lowered risk of HIV infection almost since the beginning of the HIV/AIDS epidemic.1 Results from a randomised controlled trial in South Africa in 2005 indicate that male circumcision protects men against the acquisition of HIV through heterosexual intercourse,2 confirming the findings from 20 years of observational studies.3 Circumcised men in the South African trial were 60% (...) less likely to acquire HIV than their uncircumcised counterparts. A mathematical modelling study, based on the South African trial, estimates that the practice of male circumcision could avert two million new HIV infections and 300 000 HIV-related deaths over the next 10 years in sub-Saharan Africa.4 More recently, two randomised controlled trials in Kisumu, Kenya and Rakai, Uganda showed, respectively, 53% and 48% reductions in HIV acquisition among circumcised men than uncircumcised men in the trial.5 These results strongly suggest that male circumcision could play an important role in the struggle against the continued rise in new HIV infections. However, as observers noted at the 2006 XVI International AIDS Conference in Toronto, Canada, excitement about the potential epidemiological impact has overshadowed the debate over the difficult translation of research on male circumcision, into policy and practice.6 Similar calls for caution have been raised before and elsewhere.7,8The topic of male circumcision carries an enormous amount of ethical baggage. Male infants, worldwide, are circumcised for various medical, social and/or religious reasons. Circumcision is a cultural act and a surgical procedure; medical reasons are not the only reasons to circumcise that people have found and continue to find as compelling. Benatar and Benatar9 have argued that—when …. (shrink)

The article presents the results of research activities which were undertaken in Volgograd Medical University to celebrate the World Bioethics Day. The theme of scientific events organized on the basis of the Department of Bioethics, Philosophy and Medical Law with a course of the sociology of medicine with the participation of the Department of Ethical, Legal and Sociological Expertise in Medicine of Volgograd Medical Scientific Center is “Benefit and Harm”. The article presents the Program of holding a scientific online conference (...) with international participation and the results of the essay competition among students and young scientists. (shrink)