Classical logic, argument and dialectic

A well studied instantiation of Dung's abstract theory of argumentation yields argumentation-based characterisations of non-monotonic inference over possibly inconsistent sets of classical formulae. This provides for single-agent reasoning in terms of argument and counter-argument, and distributed non-monotonic reasoning in the form of dialogues between computational and/or human agents. However, features of existing formalisations of classical logic argumentation (Cl-Arg) that ensure satisfaction of rationality postulates, preclude applications of Cl-Arg that account for real-world dialectical uses of arguments by resource-bounded agents. This paper formalises dialectical classical logic argumentation that both satisfies these practical desiderata and is provably rational. In contrast to standard approaches to Cl-Arg we: 1) draw an epistemic distinction between an argument's premises accepted as true, and those assumed true for the sake of argument, so formalising the dialectical move whereby arguments\u2019 premises are shown to be inconsistent, and avoiding the foreign commitment problem that arises in dialogical applications; 2) provide an account of Cl-Arg suitable for real-world use by eschewing the need to check that an argument's premises are subset minimal and consistent, and identifying a minimal set of assumptions as to the arguments that must be constructed from a set of formulae in order to ensure that the outcome of evaluation is rational. We then illustrate our approach with a natural deduction proof theory for propositional classical logic that allows measurement of the \u2018depth\u2019 of an argument, such that the construction of depth-bounded arguments is a tractable problem, and each increase in depth naturally equates with an increase in the inferential capabilities of real-world agents. We also provide a resource-bounded argumentative characterisation of non-monotonic inference as defined by Brewka's Preferred Subtheories

Quantum Statistical Entropy and Minimal Length of 5D Ricci-flat Black String with Generalized Uncertainty Principle

In this paper, we study the quantum statistical entropy in a 5D Ricci-flat black string solution, which contains a 4D Schwarzschild-de Sitter black hole on the brane, by using the improved thin-layer method with the generalized uncertainty principle. The entropy is the linear sum of the areas of the event horizon and the cosmological horizon without any cut-off and any constraint on the bulk's configuration rather than the usual uncertainty principle. The system's density of state and free energy are convergent in the neighborhood of horizon. The small-mass approximation is determined by the asymptotic behavior of metric function near horizons. Meanwhile, we obtain the minimal length of the position $\Delta x$ which is restrained by the surface gravities and the thickness of layer near horizons.Comment: 11pages and this work is dedicated to the memory of Professor Hongya Li

Black String Perturbations in RS1 Model

We present a general formalism for black string perturbations in Randall-Sundrum 1 model (RS1). First, we derive the master equation for the electric part of the Weyl tensor $E_{\mu\nu}$. Solving the master equation using the gradient expansion method, we give the effective Teukolsky equation on the brane at low energy. It is useful to estimate gravitational waves emitted by perturbed rotating black strings. We also argue the effect of the Gregory-Laflamme instability on the brane using our formalism.Comment: 14 pages, Based on a talk presented at ACRGR4, the 4th Australasian Conference on General Relativity and Gravitation, Monash University, Melbourne, January 2004. To appear in the proceedings, in General Relativity and Gravitatio

Introducing Preference-Based Argumentation to Inconsistent Ontological Knowledge Bases

International audienceHandling inconsistency is an inherent part of decision making in traditional agri-food chains – due to the various concerns involved. In order to explain the source of inconsistency and represent the existing conflicts in the ontological knowledge base, argumentation theory can be used. However, the current state of art methodology does not allow to take into account the level of significance of the knowledge expressed by the various ontological knowledge sources. We propose to use preferences in order to model those differences between formulas and evaluate our proposal practically by implementing it within the INRA platform and showing a use case using this formalism in a bread making decision support system

Brick Walls on the Brane

The so-called ``brick-wall model'' is a semi-classical approach that has been used to explain black hole entropy in terms of thermal matter fields. Here, we apply the brick-wall formalism to thermal bulk fields in a Randall-Sundrum brane world scenario. In this case, the black hole entity is really a string-like object in the anti-de Sitter bulk, while appearing as a Schwarzchild black hole to observers living on the brane. In spite of these exotic circumstances, we establish that the Bekenstein-Hawking entropy law is preserved. Although a similar calculation was recently considered in the literature, this prior work invoked a simplifying assumption (which we avoid) that can not be adequately justified.Comment: 18 pages, Latex; references and discussion added but conclusions unchanged; references missing in V4 have been restore

In the wild pilot usability assessment of a connected health system for stroke self management

UK Engineering Physical Sciences Research Council (EPSRC) under grant EP/P010105/1

Goal-Driven Structured Argumentation for Patient Management in a Multimorbidity Setting

We use computational argumentation to both analyse and generate solutions for reasoning in multimorbidity about consistent recommendations, according to different patient-centric goals. Reasoning in this setting carries a complexity related to the multiple variables involved. These variables reflect the co-existing health conditions that should be considered when defining a proper therapy. However, current Clinical Decision Support Systems (CDSSs) are not equipped to deal with such a situation. They do not go beyond the straightforward application of the rules that build their knowledge base and simple interpretation of Computer-Interpretable Guidelines (CIGs). We provide a computational argumentation system equipped with goal-seeking mechanisms to combine independently generated recommendations, with the ability to resolve conflicts and generate explanations for its results. We also discuss its advantages over and relation to Multiple-criteria Decision-making (MCDM) in this particular setting.- (undefined