Probability, propensity and probabilities of propensities (and of probabilities)

The process of doing Science in condition of uncertainty is illustrated with a toy experiment in which the inferential and the forecasting aspects are both present. The fundamental aspects of probabilistic reasoning, also relevant in real life applications, arise quite naturally and the resulting discussion among non-ideologized, free-minded people offers an opportunity for clarifications.Comment: Invited contribution to the proceedings MaxEnt 2016 based on the talk given at the workshop (Ghent, Belgium, 10-15 July 2016), supplemented by work done within the program Probability and Statistics in Forensic Science at the Isaac Newton Institute for Mathematical Sciences, Cambridg

Teaching statistics in the physics curriculum: Unifying and clarifying role of subjective probability

Subjective probability is based on the intuitive idea that probability quantifies the degree of belief that an event will occur. A probability theory based on this idea represents the most general framework for handling uncertainty. A brief introduction to subjective probability and Bayesian inference is given, with comments on typical misconceptions which tend to discredit it and comparisons to other approaches.Comment: 15 pages, LateX, 1 eps figure, corrected some typos. Invited paper for the American Journal of Physics. This paper and related work are also available at http://www-zeus.roma1.infn.it/~agostini

Display of diagnostic information from multiple viewpoints in an anomalous situation of complex plants

The paper describes the objectives, approaches, and current status of an intelligent information display agent called semantic representation interface (SI). The SI displays diagnostic information from a functional viewpoint as well as from behavioral, operational, and structural ones to plant operators in an anomalous situation. The functional information of the plant will help operators to understand the overall plant situation and the necessity of a recommended counter action written in operation manuals or suggested by the SI. Diagnostic information of anomaly identification and finding possible counter actions are derived by qualitative reasoning based on a functional model. The selection of suitable counter actions which will be developed in the near future is made using a fast future prediction code generated by an intelligent modular simulation system. The derived diagnostic information is displayed in a graphical way so that an operator can understand the information as a pattern. In addition to the graphical display, necessary graphs to understand the plant situation and the derived diagnostic information are automatically shown. The applicability of the diagnostic techniques applied the qualitative reasoning is discussed through applications to an oil refinery plant</p

Bounded Rationality for Data Reasoning based on Formal Concept Analysis

Formal Concept Analysis (FCA) is a theory whose goal is to discover and extract Knowledge from qualitative data. It also provides tools for sound reasoning (implication basis and association rules). The aim of this paper is to apply FCA to a new model for bounded rationality based on the implicational reasoning over contextual knowledge bases which are obtained from contextual selections. A contextual selection is a selection of events and attributes about them which induces partial contexts from a global formal context. In order to avoid inconsistencies, association rules are selected as reasoning engine. The model is applied to forecast sport results.Ministerio de Ciencia e Innovación TIN2009-09492Junta de Andalucía TIC-606

THE DEVELOPMENT OF A HOLISTIC EXPERT SYSTEM FOR INTEGRATED COASTAL ZONE MANAGEMENT

Coastal data and information comprise a massive and complex resource, which is vital to the practice of Integrated Coastal Zone Management (ICZM), an increasingly important application. ICZM is just as complex, but uses the holistic paradigm to deal with the sophistication. The application domain and its resource require a tool of matching characteristics, which is facilitated by the current wide availability of high performance computing. An object-oriented expert system, COAMES, has been constructed to prove this concept. The application of expert systems to ICZM in particular has been flagged as a viable challenge and yet very few have taken it up. COAMES uses the Dempster- Shafer theory of evidence to reason with uncertainty and importantly introduces the power of ignorance and integration to model the holistic approach. In addition, object orientation enables a modular approach, embodied in the inference engine - knowledge base separation. Two case studies have been developed to test COAMES. In both case studies, knowledge has been successfully used to drive data and actions using metadata. Thus a holism of data, information and knowledge has been achieved. Also, a technological holism has been proved through the effective classification of landforms on the rapidly eroding Holderness coast. A holism across disciplines and CZM institutions has been effected by intelligent metadata management of a Fal Estuary dataset. Finally, the differing spatial and temporal scales that the two case studies operate at implicitly demonstrate a holism of scale, though explicit means of managing scale were suggested. In all cases the same knowledge structure was used to effectively manage and disseminate coastal data, information and knowledge

08091 Abstracts Collection -- Logic and Probability for Scene Interpretation

From 25.2.2008 to Friday 29.2.2008, the Dagstuhl Seminar 08091 ``Logic and Probability for Scene Interpretation\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper