Retailing combines complicated communication skills and strategies to reach an agreement between buyer and seller with identical or different goals. In each transaction a good seller finds an optimal solution by considering his/her own profits while simultaneously considering whether the buyer's needs have been met. In this paper, we manage the retailing problem by mixing cooperation and competition. We present a rich dataset of buyer-seller bargaining in a simulated marketplace in which each agent values goods and utility separately. Various attributes (preference, quality, and profit) are initially hidden from one agent with respect to its role; during the conversation, both sides may reveal, fake, or retain the information uncovered to come to a final decision through natural language. Using this dataset, we leverage transfer learning techniques on a pretrained, end-to-end model and enhance its decision-making ability toward the best choice in terms of utility by means of multi-agent reinforcement learning. An automatic evaluation shows that our approach results in more optimal transactions than human does. We also show that our framework controls the falsehoods generated by seller agents.

Conversational AI for Positive-sum Retailing under Falsehood Control

**Organizers:** Bing Liu, Alexandros Papangelis, Stefan Ultes, Abhinav Rastogi, Yun-Nung (Vivian) Chen,
Georgios Spithourakis, Elnaz Nouri, Weiyan Shi **Description:** Over the past decades, mathematicians, linguists, and computer scientists have dedicated their efforts towards empowering
human-machine communication in natural language. While in recent years the emergence of virtual personal assistants
such as Siri, Alexa, Google Assistant, and Cortana has pushed the field forward, the development of such conversational
agents remains difficult with numerous unanswered questions and challenges. Following the success of the 3rd NLP
for Conversational AI workshop at EMNLP, "The 4th NLP4ConvAI” will be a one-day workshop, co-located with ACL
2022 in Dublin. The goal of this workshop is to bring together researchers and practitioners to discuss impactful research
problems in this area, share findings from real-world applications, and generate ideas for future research directions. **Please visit our [website](https://sites.google.com/view/4thnlp4convai/)**

(ConvAI) The 4th Workshop on NLP for Conversational AI

workshop paper

# Welcome everyone to ACL 2022!

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ACL 2022

The Association for Computational Linguistics (ACL) is the premier international scientific and professional society for people working on computational problems involving human language, a field often referred to as either computational linguistics or natural language processing (NLP). 

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