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| 2. |
- Edman, Anneli, et al.
(författare)
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A Basis for a System Development Methodology for User Cooperative Systems
- 1997
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Ingår i: Proceedings of Context'97, the International and Interdisciplinary Conference on Modeling and Using Context. - : Universidade Federal do Rio de Janeiro, Rio de Janeiro. ; , s. 290-302
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Konferensbidrag (refereegranskat)abstract
- We propose a software architecture for user-cooperative systems, like knowledge systems. This architecture incorporates important notions for building up a context, such as cooperation, explanations and incremental knowledge acquisition. Our main concern
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| 3. |
- Edman, Anneli, et al.
(författare)
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A system architecture for knowledge-based hypermedia
- 1999
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Ingår i: INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES. - : ACADEMIC PRESS LTD. - 1071-5819. ; 51:5, s. 1007-1036
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Tidskriftsartikel (refereegranskat)abstract
- Hypermedia systems and knowledge systems can be viewed as flip-sides of the same coin. The former are designed to convey information and the latter to solve problems; developments beyond the basic techniques of each system type requires techniques from t
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| 4. |
- Edman, Anneli, et al.
(författare)
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A Web-based User Adaptive Learning Environment
- 2000
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Ingår i: Proceedings in form of a CD. - : SSGRR 2000 computer and business conference.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- We present a design structure for constructing web based user adaptive learning environments. Currently the web offers huge amounts of unstructured information but no facilities for exploiting this in a problem solving situation. Our aim is to gather and
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| 5. |
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| 6. |
- Eriksson Lundström, Jenny, et al.
(författare)
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Argumentation as a metacognitive skill of passing acceptance : a case study from a scientific dispute
- 2005
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Ingår i: Metacognition in computation : papers from the 2005 AAAI symposium. Technical Report SS-05-04. - Menlo Park, California : AAAI Press. - 9781577352303 ; , s. 74-79
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Konferensbidrag (refereegranskat)abstract
- Automated decision-making is a significant concern for theAI community and especially for multi-agent systems. Although it has long been known among scholars of rhetoric that human decision-making can be systematically influenced by skillful argumentation, there seems to be a lack of formalizations which handle the impact rhetoric has on the concealment of logical fallacies to the human mind. In this paper, we highlight the need of metacognition for the successful formal representation and interpretation of human argumentation and thus successful automated decision-making. The relevance of such investigations is illustrated with a real-world example taken from the discourse of neuroscience.
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| 7. |
- Eriksson Lundström, Jenny S. Z., 1973-
(författare)
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On the Formal Modeling of Games of Language and Adversarial Argumentation : A Logic-Based Artificial Intelligence Approach
- 2009
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Argumentation is a highly dynamical and dialectical process drawing on human cognition. Successful argumentation is ubiquitous to human interaction. Comprehensive formal modeling and analysis of argumentation presupposes a dynamical approach to the following phenomena: the deductive logic notion, the dialectical notion and the cognitive notion of justified belief. For each step of an argumentation these phenomena form networks of rules which determine the propositions to be allowed to make sense as admissible, acceptable, and accepted. We present a formal logic framework for a computational account of formal modeling and systematical analysis of the dynamical, exhaustive and dialectical aspects of adversarial argumentation and dispute. Our approach addresses the mechanisms of admissibility, acceptability and acceptance of arguments in adversarial argumentation by use of metalogic representation and Artificial Intelligence-techniques for dynamical problem solving by exhaustive search. We elaborate on a common framework of board games and argumentation games for pursuing the alternatives facing the adversaries in the argumentation process conceived as a game. The analogy to chess is beneficial as it incorporates strategic and tactical operations just as argumentation. Drawing on an analogy to board games like chess, the state space representation, well researched in Artificial Intelligence, allows for a treatment of all possible arguments as paths in a directed state space graph. It will render a game leading to the most wins and fewest losses, identifying the most effective game strategy. As an alternate visualization, the traversal of the state space graph unravels and collates knowledge about the given situation/case under dispute. Including the private knowledge of the two parties, the traversal results in an increased knowledge of the case and the perspectives and arguments of the participants. As we adopt metalogic as formal basis, arguments used in the argumentation, expressed in a non-monotonic defeasible logic, are encoded as terms in the logical argumentation analysis system. The advantage of a logical formalization of argumentation is that it provides a symbolic knowledge representation with a formally well-formed semantics, making the represented knowledge as well as the behavior of knowledge representation systems reasoning comprehensible. Computational logic as represented in Horn Clauses allows for expression of substantive propositions in a logical structure. The non-monotonic nature of defeasible logic stresses the representational issues, i.e. what is possible to capture in non-monotonic reasoning, while from the (meta)logic program, the sound computation on what it is possible to compute, and how to regard the semantics of this computation, are established.
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| 8. |
- Eriksson Lundström, Jenny, 1973-, et al.
(författare)
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Towards a dynamic metalogic implementation of legal argumentation
- 2011
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Ingår i: The proceedings of the 13<sup>th</sup> International Conference on Artificial Intelligence and Law, Pittsburgh, PA, USA, June 3-10, 2011.. - New York, NY, USA : ACM. - 9781450307550 ; , s. 91-95
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Konferensbidrag (refereegranskat)abstract
- Human argumentation in general and legal dispute in particular can be seen as highly dynamic and non-monotonic to its nature. To us this suggests that logical analysis of legal argumentation needs to be conducted in a dynamical and flexible setting in which the interaction is influenced by the parties' previous arguments. To express such approximations of legal reasoning as computational formalizations of argument, applications require dealing with knowledge representations, non-monotonic logics and a game-model able to capture the interaction as a debate between two or more disputing parties. In this paper we present some intuitions regarding the features of a full implementation and accompanying software for defeasible adversarial legal argumentation.
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| 9. |
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| 10. |
- Gallina, Barbara, et al.
(författare)
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Towards Explainable, Compliant and Adaptive Human-Automation Interaction
- 2020
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Ingår i: Proceedings of the 3rd EXplainable AI in Law Workshop (XAILA 2020).
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Konferensbidrag (refereegranskat)abstract
- AI-based systems use trained machine learning models to make important decisions in critical contexts. The EU guidelines for trustworthy AI emphasise the respect for human autonomy, prevention of harm, fairness, and explicability. Many successful machine learning methods, however, deliver opaque models where the reasons for decisions remain unclear to the end user. Hence, accountability and trust are difficult to ascertain. In this position paper, we focus on AI systems that are expected to interact with humans and we propose our visionary architecture, called ECA-HAI (Explainable, Compliant and Adaptive Human-Automation Interaction)-RefArch. ECA-HAI-RefArch allows for building intelligent systems where humans and AIs form teams, able to learn from data but also to learn from each other by playing “serious games”, for a continuous improvement of the overall system. Finally, conclusions are drawn.
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