Strategical Argumentative Agent for Human Persuasion: A Preliminary Report

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Automated agents should be able to persuade people in the same way people persuade each other, namely via dialog. Today, automated persuasion modeling and investigation use unnatural assumptions in persuasive interactions which create doubt regarding their applicability in real world deployment with people. In this work we present a novel methodology for persuading people through argumentative dialog. Our methodology combines theoretical argumentation modeling, machine learning and Markovian optimization techniques, which together form an innovative agent named SPA. Preliminary field experiments indicate that SPA provides higher levels of attitude change among subjects compared to two baseline agents.
Original languageAmerican English
Title of host publicationWorkshop on Frontiers and Connections between Argumentation Theory and Natural Language Processing
StatePublished - 2016

Bibliographical note

Place of conference:Germany


Dive into the research topics of 'Strategical Argumentative Agent for Human Persuasion: A Preliminary Report'. Together they form a unique fingerprint.

Cite this