Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

A framework for decision making on teleexpertise with traceability of the reasoning

This paper provides a methodological framework for decision making process to ensure its traceability generally in the context of telemedicine and particularly in the act of teleexpertise. This act permits to medical professionals and/or health professionals to collaborate in order to take suitable decisions for a patient diagnosis or treatment. The main problem dealing with teleexpertise is the following: How to ensure the traceability of the decisions making process? This problem is solved in this paper through a conceptualisation of a rigorous framework coupling semantic modelling and explicit reasoning which permits to fully support the analysis and rationale for decisions made. The logical semantic underlying this framework is the argumentative logicto provide adequate management of information with traceability of the reasoning including options and constraints. Thus our proposal will permit to formally ensure the traceability of reasoning in telemedicine and particularly in teleexpertise in order to favour the quality of telemedicine’s procedure checking. This traceability is to guarantee equitable access to the benefits of the collective knowledge and experience and to provide remote collaborative practices with a sufficient safety margin to guard against the legal requirements. An illustrative case study is provided by the modelling of a decision making process applied to teleexpertise for chronic diseases such as diabetes mellitus type2

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

Development of a Logic Layer in the Semantic Web: Research Issues

The ontology layer of the semantic web is now mature enough (i.e. standards like RDF, RDFs, OWL, OWL 2) and the next step is to work on a logic layer for the development of advanced reasoning capabilities for knowledge extraction and efficient decision making. Adding logic to the web means using rules to make inferences. Rules are a means of expressing business processes, policies, contracts etc but most of the studies have focused on the use of monotonic logics in layered development of the semantic web which provides no mechanism for representing or handling incomplete or contradictory information respectively. This paper discusses argumentation, semantic web and defeasible logic programming with their distinct features and identifies the different research issues that need to be addressed in order to realize defeasible argumentative reasoning in the semantic web applications

Conjoint utilization of structured and unstructured information for planning interleaving deliberation in supply chains

Effective business planning requires seamless access and intelligent analysis of information in its totality to allow the business planner to gain enhanced critical business insights for decision support. Current business planning tools provide insights from structured business data (i.e. sales forecasts, customers and products data, inventory details) only and fail to take into account unstructured complementary information residing in contracts, reports, user\u27s comments, emails etc. In this article, a planning support system is designed and developed that empower business planners to develop and revise business plans utilizing both structured data and unstructured information conjointly. This planning system activity model comprises of two steps. Firstly, a business planner develops a candidate plan using planning template. Secondly, the candidate plan is put forward to collaborating partners for its revision interleaving deliberation. Planning interleaving deliberation activity in the proposed framework enables collaborating planners to challenge both a decision and the thinking that underpins the decision in the candidate plan. The planning system is modeled using situation calculus and is validated through a prototype development

Hypotheses, evidence and relationships: The HypER approach for representing scientific knowledge claims

Biological knowledge is increasingly represented as a collection of (entity-relationship-entity) triplets. These are queried, mined, appended to papers, and published. However, this representation ignores the argumentation contained within a paper and the relationships between hypotheses, claims and evidence put forth in the article. In this paper, we propose an alternate view of the research article as a network of 'hypotheses and evidence'. Our knowledge representation focuses on scientific discourse as a rhetorical activity, which leads to a different direction in the development of tools and processes for modeling this discourse. We propose to extract knowledge from the article to allow the construction of a system where a specific scientific claim is connected, through trails of meaningful relationships, to experimental evidence. We discuss some current efforts and future plans in this area

Combining conceptual graphs and argumentation for aiding in the teleexpertise

Current medical information systems are too complex to be meaningfully exploited. Hence there is a need to develop new strategies for maximising the exploitation of medical data to the benefit of medical professionals. It is against this backdrop that we want to propose a tangible contribution by providing a tool which combines conceptual graphs and Dung׳s argumentation system in order to assist medical professionals in their decision making process. The proposed tool allows medical professionals to easily manipulate and visualise queries and answers for making decisions during the practice of teleexpertise. The knowledge modelling is made using an open application programming interface (API) called CoGui, which offers the means for building structured knowledge bases with the dedicated functionalities of graph-based reasoning via retrieved data from different institutions (hospitals, national security centre, and nursing homes). The tool that we have described in this study supports a formal traceable structure of the reasoning with acceptable arguments to elucidate some ethical problems that occur very often in the telemedicine domain