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- 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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| 3. |
- Ågerfalk, Pär J., 1971-, et al.
(författare)
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Artificial Intelligence in Information Systems : State of the Art and Research Roadmap
- 2022
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Ingår i: Communications of the Association for Information Systems. - : Association for Information Systems. - 1529-3181. ; 50:1, s. 420-438
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Tidskriftsartikel (refereegranskat)abstract
- Many would argue that artificial intelligence (AI) is not only technology but also a paradigmatic shift in the relationship between humans and machines. Much literature assumes that AI-powered practices substantially differ from and profoundly change organizational structures, communication, affordances, and ecosystems. However, AI research remains fragmented and often lacks clarity. While the information systems (IS) discipline can play a pivotal role in AI’s emergence and use, the discipline needs a clear direction that specifies how it can contribute and its key research themes and questions. This paper draws on a professional development workshop that we organized at the 2020 International Conference on Information Systems and the discussions that followed. We summarize and synthesize how AI has impacted organizational practices over five decades and provide views from various perspectives. We identify weaknesses in the current AI literature as measured against conceptual clarity, theoretical glue, cumulative tradition, parsimony, and applicability. We also identify direct actions that the IS research community can undertake to address these issues. Finally, we propose a next-step research agenda to guide AI research in the coming years.
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