Intelligent Techniques in Engineering Management by Cengiz Kahraman & Sezi Çevik Onar

Author:Cengiz Kahraman & Sezi Çevik Onar
Language: eng
Format: epub
Publisher: Springer International Publishing, Cham

14.2 State of the Art

14.2.1 Artificial Intelligence and Argumentation Theory Relationship

Nowadays Artificial Intelligence has been identified like one of the most important fields of application of the Argumentation Theory (Fernandez et al. 2013a, b; c, d; Fox et al. 1992; Krause et al. 1995; Dimpoulos et al. 1999; Dung 1995; Besnard and Hunter 2008; Bench-Capon and Dunne 2007; Kraus et al. 1998; Moraitis and Spanoudakis 2007; Rahwan and Simari 2009; Amgoud 2012, 2013; Atkinson et al. 2013; Azhar et al. 2013; Gabbriellini and Torroni 2013, 2014; Medellin-Gasque et al. 2013; Zeng et al. 2013). Artificial Intelligence and Argumentation Theory can be seen combined together in many other subjects like: (1) Computational models of argumentation , (2) Argument based decisions making, (3) Deliberation based on argumentation, (4) Persuasion based on argumentation, (5) Search of information for inquiring based on argumentation, (6) Negotiation and resolution of conflicts based on argumentation, (7) Analysis of risks based on argumentation (8) Legal reasoning based on argumentation, (9) Electronic democracy based on argumentation, (10) Cooperation, coordination, and team building based on argumentation, (11) Argumentation and game theory in multiagent systems , (12) Argumentation Human-Agent, (13) Modeling of preferences in argumentation, (14) Strategic behavior in argument based dialogues, (15) Deception, truthfulness and reputation in the interaction based on argumentation, (16) Computational complexity of the dialogues based on argumentation, (17) Properties of dialogues based on argumentation (success, termination, etc.), (18) Hybrid models of argumentation and (19) Implementation of multiagent systems based on argumentation.

There are two difference tendencies about automatic argumentation: (1) Abstract Argumentation and (2) Deductive Argumentation. The Abstract Argumentation is focused in the coexistence of arguments without getting into detail of its meaning. It only takes care about the attack relationships among arguments and their acceptability or not and in which grade. One of the most important studies so far and whose concepts are still valid nowadays are the Abstract Argumentation Systems of Dung (1995). Boella et al. (2006) proposed an extension of Dung’s model in which the arguments are dynamic elements not predefined in advance. Deductive Argumentation is another option to the Automatic Argumentation. Deductive models are based on formulas and based on Classical Logic. The arguments, opposite to the Abstract Argumentation, are complex elements that can be subdivided in elements or arguments of more simple structure. Deductive Argumentation is able to manage the complexity of the internal structure of the arguments. The key concept inside this type of argumentation is the logical deduction. The fundamental objective of whatever model of deductive argumentation is to reach a conclusion based on a support formed by arguments and reasoning of deductive logic. In the literature we find a recent study carried out by Besnard and Hunter (2008) which is focused on Deductive Argumentation inside the area of Artificial intelligence . Deductive Argumentation is about how to manage non evident information (information that is not known if it is or not acceptable or truthful) and should generate arguments to support or against this information so that after a process of deductive reasoning, the conclusion about its truthfulness or admissibility is reached.

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