论文标题
改进与人格建模谈判的对话系统
Improving Dialog Systems for Negotiation with Personality Modeling
论文作者
论文摘要
在本文中，我们探讨了对对手进行建模和推断人格类型，预测他们的反应的能力，并使用此信息来适应对话代理在谈判任务中的高级策略。受到将思想理论（TOM）纳入机器的想法的启发，我们引入了一种概率表述，以在学习和推理过程中封装对手的人格类型。我们在Craigslistbargain数据集上测试了我们的方法，并表明我们使用TOM推断的方法比混合对手种群的基线比对话率提高了20％。我们还发现，我们的模型以不同类型的对手的方式显示了各种各样的谈判行为。
In this paper, we explore the ability to model and infer personality types of opponents, predict their responses, and use this information to adapt a dialog agent's high-level strategy in negotiation tasks. Inspired by the idea of incorporating a theory of mind (ToM) into machines, we introduce a probabilistic formulation to encapsulate the opponent's personality type during both learning and inference. We test our approach on the CraigslistBargain dataset and show that our method using ToM inference achieves a 20% higher dialog agreement rate compared to baselines on a mixed population of opponents. We also find that our model displays diverse negotiation behavior with different types of opponents.
