Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Proceedings of the Inaugural Meeting ofAIS SIGPrag

The Special Interest Group on Pragmatist IS Research (SIGPrag) was approved by the Association for InformationSystems (AIS) council at its June 2008 meeting in Gallway. The motivation for this initiative is the growingrecognition of the importance of theorizing the IT artifact and its organizational and societal context from apragmatic and action-oriented perspective. SIGPrag\u27s mission is to provide a much-needed centre of gravity and tofacilitate exchange of ideas and further development of this area of IS scholarship.In summary, pragmatist IS research rests on the following set of assumptions: * Human life is a life of activity.* Humans do things that effect changes in their environment and/or within themselves.* Doing permeates thinking, conceptualizations and language use.* Human consciousness is a practical one that is in constant interplay with interventive, investigative, andevaluative actions.* Practical consciousness is formed by experience from previous actions and participation in social contexts.* IT and information systems are fundamentally symbolic language systems.* Linguistically expressed collective presuppositions, norms and categories (such as those embedded in ITand information systems) serve human activity and life.* The true value of IT and information systems lies in their potential to support human communication andcollaboration central to human activity and life.For more information about SIGPrag, its mission and current activities, please visit http://www.sigprag.org/The inaugural meeting of SIGPrag is to be held in Paris on Dec 14, 2008, in conjunction with the InternationalConference on Information Systems (ICIS). The meeting will consist of two parts, a scientific meeting and abusiness meeting. For the scientific meeting a call for position papers was issued in the summer of 2008, whichresulted in the following papers being selected for presentation:• What Kind of Pragmatism in Information Systems Research? by Göran Goldkuhl.• Pragmatic Approach in IS Projects Grounded on Recognised Frameworks by Raija Halonen.• Co-Design as Social Constructive Pragmatism by Mikael Lind, Ulf Seigerroth, Olov Forsgren, and AndersHjalmarsson.• Pragmatism and Information Systems (IS): Neurophilosophical approach by Garikoitz Lerma Usabiagaand Francesc Miralles.• Sustainability Communication: A role for IT and IS in relating business and Society by Mark Aakhus andPaul Ziek.• Managing Ambiguity while Reducing Uncertainty by Gianni Jacucci and Mike Martin.• A Pragmatic Conception of Service Encounters by Mikael Lind and Nicklas Salomonson.• Making the Web More Pragmatic: Exploring the Potential Of Some Pragmatic Concepts For IS ResearchAnd Development by Jens Allwood and Mikael Lind.• Introducing Human in Complex System: A Cognitive Pragmatics Based Model by G. Lortal.• The Pragmatic Web: An Application View by Mareike Schoop.• Design Research from a Communicative Perspective: How to Design Things with Words by Hans Weigand.• Representation and Correspondence: On the Validity of the Representation Assumption in InformationSystem Design by Pär J. Ågerfalk and Owen Eriksson.• Habermas’ theory in action by Jan L.G. Dietz.• Challenges to Information Systems Development by Roland Kaschek.The idea behind this inaugural meeting was to bring together people that share an affinity with pragmatist ISresearch and to initiate a scientific discussion about the role of pragmatist research in IS. We certainly hope that thisdiscussion will continue over the years to come. The papers are freely available for download athttp://www.sigprag.org

Computer Aided Diagnostic Support System for Skin cancer: Review of techniques and algorithms

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique’s performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided

Computer aided diagnostic support system for skin cancer: A review of techniques and algorithms

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided. © 2013 Ammara Masood and Adel Ali Al-Jumaily