On the interplay between games, argumentation and dialogues

Game theory, argumentation and dialogues all address problems concerning inter-agent interaction, but from different perspectives. In this paper, we contribute to the study of the interplay between these fields. In particular, we show that by mapping games in normal form into structured argumentation, computing dominant solutions and Nash equilibria is equivalent to computing admissible sets of arguments. Moreover, when agents lack complete information, computing dominant solutions/Nash equilibria is equivalent to constructing successful (argumentation-based) dialogues. Finally, we study agents’ behaviour in these dialogues in reverse game-theoretic terms and show that, using specific notions of utility, agents engaged in (argumentation-based) dialogues are guaranteed to be truthful and disclose relevant information, and thus can converge to dominant solutions/Nash equilibria of the original games even under incomplete information

Strategic Argumentation Dialogues for Persuasion: Framework and Experiments Based on Modelling the Beliefs and Concerns of the Persuadee

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is good in a particular dialogue are the degree to which the intended audience believes the argument and counterarguments, and the impact that the argument has on the concerns of the intended audience. In this paper, we present a framework for modelling persuadees in terms of their beliefs and concerns, and for harnessing these models in optimizing the choice of move in persuasion dialogues. Our approach is based on the Monte Carlo Tree Search which allows optimization in real-time. We provide empirical results of a study with human participants showing that our automated persuasion system based on this technology is superior to a baseline system that does not take the beliefs and concerns into account in its strategy.Comment: The Data Appendix containing the arguments, argument graphs, assignment of concerns to arguments, preferences over concerns, and assignment of beliefs to arguments, is available at the link http://www0.cs.ucl.ac.uk/staff/a.hunter/papers/unistudydata.zip The code is available at https://github.com/ComputationalPersuasion/MCC

Strategic argumentation dialogues for persuasion: Framework and experiments based on modelling the beliefs and concerns of the persuadee

Persuasion is an important and yet complex aspect of human intelligence. When undertaken through dialogue, the deployment of good arguments, and therefore counterarguments, clearly has a significant effect on the ability to be successful in persuasion. Two key dimensions for determining whether an argument is 'good' in a particular dialogue are the degree to which the intended audience believes the argument and counterarguments, and the impact that the argument has on the concerns of the intended audience. In this paper, we present a framework for modelling persuadees in terms of their beliefs and concerns, and for harnessing these models in optimizing the choice of move in persuasion dialogues. Our approach is based on the Monte Carlo Tree Search which allows optimization in real-time. We provide empirical results of a study with human participants that compares an automated persuasion system based on this technology with a baseline system that does not take the beliefs and concerns into account in its strategy

Negotiating with a logical-linguistic protocol in a dialogical framework

This book is the result of years of reflection. Some time ago, while working in commodities, the author felt how difficult it was to decide the order in which to use arguments during a negotiation process. What would happen if we translated the arguments into cards and played them according to the rules of the Bridge game? The results were impressive. There was potential for improvement in the negotiation process. The investigation went deeper, exploring players, cards, deals and the information concealed in the players´ announcements, in the cards and in the deals. This new angle brought the research to NeuroLinguistic Patterns and cryptic languages, such as Russian Cards. In the following pages, the author shares her discovery of a new application for Logical Dialogues: Negotiations, tackled from basic linguistic structures placed under a dialogue form as a cognitive system which ‘understands’ natural language, with the aim to solve conflicts and even to serve peace