64 research outputs found

    Intentional dialogues in multi-agent systems based on ontologies and argumentation

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    Some areas of application, for example, healthcare, are known to resist the replacement of human operators by fully autonomous systems. It is typically not transparent to users how artificial intelligence systems make decisions or obtain information, making it difficult for users to trust them. To address this issue, we investigate how argumentation theory and ontology techniques can be used together with reasoning about intentions to build complex natural language dialogues to support human decision-making. Based on such an investigation, we propose MAIDS, a framework for developing multi-agent intentional dialogue systems, which can be used in different domains. Our framework is modular so that it can be used in its entirety or just the modules that fulfil the requirements of each system to be developed. Our work also includes the formalisation of a novel dialogue-subdialogue structure with which we can address ontological or theory-of-mind issues and later return to the main subject. As a case study, we have developed a multi-agent system using the MAIDS framework to support healthcare professionals in making decisions on hospital bed allocations. Furthermore, we evaluated this multi-agent system with domain experts using real data from a hospital. The specialists who evaluated our system strongly agree or agree that the dialogues in which they participated fulfil Cohen’s desiderata for task-oriented dialogue systems. Our agents have the ability to explain to the user how they arrived at certain conclusions. Moreover, they have semantic representations as well as representations of the mental state of the dialogue participants, allowing the formulation of coherent justifications expressed in natural language, therefore, easy for human participants to understand. This indicates the potential of the framework introduced in this thesis for the practical development of explainable intelligent systems as well as systems supporting hybrid intelligence

    MAIDS - a Framework for the Development of Multi-Agent Intentional Dialogue Systems

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    This paper introduces a framework for programming highly sophisticated multi-agent dialogue systems. The framework is based on a multi-part agent belief base consisting of three components: (i) the main component is an extension of an agent-oriented programming belief base for representing defeasible knowledge and, in partic- ular, argumentation schemes; (ii) an ontology component where existing OWL ontologies can be instantiated; and (iii) a theory of mind component where agents keep track of mental attitudes they ascribe to other agents. The paper formalises a structured argumentation-based dialogue game where agents can “digress” from the main dialogue into subdialogues to discuss ontological or theory of mind issues. We provide an example of a dialogue with an ontological digression involving humans and agents, including a chatbot that we developed to support bed allocation in a hospital; we also comment on the initial evaluation of that chatbot carried out by domain experts. That example is also used to show that our framework supports all features of recent desiderata for future dialogue systems.This research was partially funded by CNPq, CAPES, FCT CEECIND /01997/2017 and UIDB/00057/2020

    Methods and tools for analysis and management of risks and regulatory compliance in the healthcare sector: the hospital at home – HaH

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    Changing or creating an organisation means creating a new process. Each process involves many risks that need to be identified and managed. The main risks considered here are procedural and legal risks. The former are related to the risks of errors that may occur during processes, while the latter are related to the compliance of processes with regulations. Managing the risks implies proposing changes to the processes that allow the desired result: an optimised process. In order to manage a company and optimise it in the best possible way, not only should the organisational aspect, risk management and legal compliance be taken into account, but it is important that they are all analysed simultaneously with the aim of finding the right balance that satisfies them all. This is the aim of this thesis, to provide methods and tools to balance these three characteristics, and to enable this type of optimisation, ICT support is used. This work isn’t a thesis in computer science or law, but rather an interdisciplinary thesis. Most of the work done so far is vertical and in a specific domain. The particularity and aim of this thesis is not to carry out an in-depth analysis of a particular aspect, but rather to combine several important aspects, normally analysed separately, which however have an impact and influence each other. In order to carry out this kind of interdisciplinary analysis, the knowledge base of both areas was involved and the combination and collaboration of different experts in the various fields was necessary. Although the methodology described is generic and can be applied to all sectors, the case study considered is a new type of healthcare service that allows patients in acute disease to be hospitalised to their home. This provide the possibility to perform experiments using real hospital database

    On the role of Computational Logic in Data Science: representing, learning, reasoning, and explaining knowledge

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    In this thesis we discuss in what ways computational logic (CL) and data science (DS) can jointly contribute to the management of knowledge within the scope of modern and future artificial intelligence (AI), and how technically-sound software technologies can be realised along the path. An agent-oriented mindset permeates the whole discussion, by stressing pivotal role of autonomous agents in exploiting both means to reach higher degrees of intelligence. Accordingly, the goals of this thesis are manifold. First, we elicit the analogies and differences among CL and DS, hence looking for possible synergies and complementarities along 4 major knowledge-related dimensions, namely representation, acquisition (a.k.a. learning), inference (a.k.a. reasoning), and explanation. In this regard, we propose a conceptual framework through which bridges these disciplines can be described and designed. We then survey the current state of the art of AI technologies, w.r.t. their capability to support bridging CL and DS in practice. After detecting lacks and opportunities, we propose the notion of logic ecosystem as the new conceptual, architectural, and technological solution supporting the incremental integration of symbolic and sub-symbolic AI. Finally, we discuss how our notion of logic ecosys- tem can be reified into actual software technology and extended towards many DS-related directions

    Methods and tools for analysis and management of risks and regulatory compliance in the healthcare sector: the Hospital at Home – HaH

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    Changing or creating a new organization means creating a new process. Each process involves many risks that need to be identified and managed. The main risks considered here are procedural risks and legal risks. The former are related to the risks of errors that may occur during processes, while the latter are related to the compliance of processes with regulations. Therefore, managing the risks implies proposing changes to the processes that allow the desired result: an optimized process. In order to manage a company and optimize it in the best possible way, not only should the organizational aspect, risk management and legal compliance be taken into account, but it is important that they are all analyzed simultaneously with the aim of finding the right balance that satisfies them all. This is exactly the aim of this thesis, to provide methods and tools to balance these three characteristics, and to enable this type of optimization, ICT support is used. This work is not intended to be a computer science or law thesis but an interdisciplinary thesis. Most of the work done so far is vertical and in a specific domain. The particularity and aim of this thesis is not so much to carry out an in-depth analysis of a particular aspect, but rather to combine several important aspects, normally analyzed separately, which however have an impact on each other and influence each other. In order to carry out this kind of interdisciplinary analysis, the knowledge base of both areas was involved and the combination and collaboration of different experts in the various fields was necessary. Although the methodology described is generic and can be applied to all sectors, a particular use case was chosen to show its application. The case study considered is a new type of healthcare service that allows patients in acute disease to be hospitalized to their home. This provide the possibility to perform experiments using real hospital database

    Automated Deduction – CADE 28

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    This open access book constitutes the proceeding of the 28th International Conference on Automated Deduction, CADE 28, held virtually in July 2021. The 29 full papers and 7 system descriptions presented together with 2 invited papers were carefully reviewed and selected from 76 submissions. CADE is the major forum for the presentation of research in all aspects of automated deduction, including foundations, applications, implementations, and practical experience. The papers are organized in the following topics: Logical foundations; theory and principles; implementation and application; ATP and AI; and system descriptions

    Computational Complexity of Strong Admissibility for Abstract Dialectical Frameworks

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    Abstract dialectical frameworks (ADFs) have been introduced as a formalism for modeling and evaluating argumentation allowing general logical satisfaction conditions. Different criteria used to settle the acceptance of arguments arecalled semantics. Semantics of ADFs have so far mainly been defined based on the concept of admissibility. Recently, the notion of strong admissibility has been introduced for ADFs. In the current work we study the computational complexityof the following reasoning tasks under strong admissibility semantics. We address 1. the credulous/skeptical decision problem; 2. the verification problem; 3. the strong justification problem; and 4. the problem of finding a smallest witness of strong justification of a queried argument

    Compliance checking in reified IO logic via SHACL

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    Reified Input/Output (I/O) logic[21] has been recently proposed to model real-world norms in terms of the logic in [11]. This is massively grounded on the notion of reification, and it has specifically designed to model meaning of natural language sentences, such as the ones occurring in existing legislation. This paper presents a methodology to carry out compliance checking on reified I/O logic formulae. These are translated in SHACL (Shapes Constraint Language) shapes, a recent W3C recommendation to validate and reason with RDF triplestores. Compliance checking is then enforced by validating RDF graphs describing states of affairs with respect to these SHACL shapes
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