Markov Games for Persuasive Dialogue

被引：6

作者：

Rach, Niklas ^{[1
]}

Minker, Wolfgang ^{[1
]}

Ultes, Stefan ^{[2
]}

机构：

[1] Ulm Univ, Inst Commun Engn, Ulm, Germany

[2] Univ Cambridge, Dept Engn, Cambridge, England

来源：

COMPUTATIONAL MODELS OF ARGUMENT (COMMA 2018) | 2018年 / 305卷

关键词：

Persuasive Dialogue; Markov Games; Reinforcement Learning;

D O I：

10.3233/978-1-61499-906-5-213

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This work discusses the formulation of argumentative dialogue as Markov game. We show how formal systems for persuasive dialogues that adhere to a certain structure can be reformulated as Markov games and thus be addressed as Reinforcement Learning task in a multi-agent setting. We validate our approach on an implementation of a proof of principle scenario where we show that the optimal policy can be learned.

引用

页码：213 / 220

页数：8

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