On argumentation schemes and the natural classification of arguments

We develop conceptions of arguments and of argument types that will, by serving as the basis for developing a natural classification of arguments, benefit work in artificial intelligence. Focusing only on arguments construed as the semantic entities that are the outcome of processes of reasoning, we outline and clarify our view that an argument is a proposition that represents a fact as both conveying some other fact and as doing so wholly. Further, we outline our view that, with respect to arguments that are propositions, (roughly) two arguments are of the same type if and only if they represent the same relation of conveyance and do so in the same way. We then argue for our conceptions of arguments and argument types, and compare them to rival positions. We also illustrate the need for, and some of the strengths of, our approach to classifying arguments through an examination of aspects of two prominent and recent attempts to classify arguments using argumentation schemes, namely those of M. Kienpointner and D. Walton. Finally, we clarify how our conception of arguments and of argument types can assist in developing an exhaustive classification of arguments

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Erratum: The development of support intuitions and object causality in juvenile Eurasian jays (Garrulus glandarius).

Knowledge about the causal relationship between objects has been studied extensively in human infants, and more recently in adult animals using differential looking time experiments. How knowledge about object support develops in non-human animals has yet to be explored. Here, we studied the ontogeny of support relations in Eurasian jays (Garrulus glandarius), a bird species known for its sophisticated cognitive abilities. Using an expectancy violation paradigm, we measured looking time responses to possible and impossible video and image stimuli. We also controlled for experience with different support types to determine whether the emergence of support intuitions is dependent upon specific interactions with objects, or if reasoning develops independently. At age 9 months, birds looked more at a tool moving a piece of cheese that was not in contact than one that was in direct contact. By the age of 6 months, birds that had not experienced string as a support to hold up objects looked more at impossible images with string hanging from below (unsupported), rather than above (supported). The development of support intuitions may be independent of direct experience with specific support, or knowledge gained from interactions with other objects may be generalised across contexts

Causality in concurrent systems

Concurrent systems identify systems, either software, hardware or even biological systems, that are characterized by sets of independent actions that can be executed in any order or simultaneously. Computer scientists resort to a causal terminology to describe and analyse the relations between the actions in these systems. However, a thorough discussion about the meaning of causality in such a context has not been developed yet. This paper aims to fill the gap. First, the paper analyses the notion of causation in concurrent systems and attempts to build bridges with the existing philosophical literature, highlighting similarities and divergences between them. Second, the paper analyses the use of counterfactual reasoning in ex-post analysis in concurrent systems (i.e. execution trace analysis).Comment: This is an interdisciplinary paper. It addresses a class of causal models developed in computer science from an epistemic perspective, namely in terms of philosophy of causalit

Agent based mobile negotiation for personalized pricing of last minute theatre tickets

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.This paper proposes an agent based mobile negotiation framework for personalized pricing of last minutes theatre tickets whose values are dependent on the time remaining to the performance and the locations of potential customers. In particular, case based reasoning and fuzzy cognitive map techniques are adopted in the negotiation framework to identify the best initial offer zone and adopt multi criteria decision in the scoring function to evaluate offers. The proposed framework is tested via a computer simulation in which personalized pricing policy shows higher market performance than other policies therefore the validity of the proposed negotiation framework.The Ministry of Education, Science and Technology (Korea

Public health reasoning: a logical view of trust

The public has a pact with the experts who deliver public health. That pact can be characterized as a relationship of trust in which the public trusts health experts to act in its best interests in return for its adherence to recommendations and other advice. This relationship clearly has emotional elements, as evidenced by strong feelings of anger and betrayal when public health recommendations are shown to be wrong. But it also has rational or logical components which are less often acknowledged by commentators. In this paper, these components are examined with special emphasis on the role of authority arguments in mediating the trust relationship between health experts and the public. It is contended that these arguments function as cognitive heuristics in that they facilitate decision-making in the absence of expert knowledge. A questionnaire study of public health reasoning was conducted in 879 members of the public. Participants were asked to consider a number of public health scenarios in which various arguments from authority were employed. Epistemic conditions, known to be associated with the rational warrant of these arguments, were systematically varied across these scenarios. Quantitative and qualitative data analyses revealed that subjects are adept at recognizing the conditions under which arguments from authority are more or less rationally warranted. The trust relationship at the heart of public health has logical components which lay people are capable of rationally evaluating during public health deliberations. This rational capacity should be exploited by experts during public health communication

Using resource graphs to represent conceptual change

We introduce resource graphs, a representation of linked ideas used when reasoning about specific contexts in physics. Our model is consistent with previous descriptions of resources and coordination classes. It can represent mesoscopic scales that are neither knowledge-in-pieces or large-scale concepts. We use resource graphs to describe several forms of conceptual change: incremental, cascade, wholesale, and dual construction. For each, we give evidence from the physics education research literature to show examples of each form of conceptual change. Where possible, we compare our representation to models used by other researchers. Building on our representation, we introduce a new form of conceptual change, differentiation, and suggest several experimental studies that would help understand the differences between reform-based curricula.Comment: 27 pages, 14 figures, no tables. Submitted for publication to the Physical Review Special Topics Physics Education Research on March 8, 200