Natural conversation is a hallmark of intelligent systems and thus dialog systems have been a key sub-area of Artificial Intelligence research for decades. Chatbots are their most recent incarnation and have been widely adopted, particularly in the recent COVID-19 pandemic, as sources of information. Given the increasing interest, there has been a surge in the development of easy-to-use platforms to rapidly create simple rule-based dialog agents. Given the rapid advances in natural language generation models, there is a great need to foster and guide the research on the development and deployment of dialog systems.
In addition to their applications in Companion Technology, chatbots have been increasingly used for providing assistance and advice during the COVID-19 pandemic. The aim is to implement technical systems that smartly adapt their functionality to their users’ individual needs and requirements and solve problems in close co-operation with users. They need to enter into a dialog and convincingly explain their suggestions and decision-making behavior.
Given their widespread adoption, there is a need to build dialog systems that can explain their reasoning and can stand up to ethical standards demanded in real-life settings. Despite the impressive applications of chatbots, the wider problem of dialog management is unaddressed, with mainstream tools supporting rudimentary rule-based processing. There is an urgent need to highlight the crucial role of reasoning methods, like constraints satisfaction, planning, and scheduling can play to build an end-to-end conversation system that evolves over time.
The workshop is the fourth edition of the Workshop on Reasoning and Learning for Human-Machine Dialogues. The past editions of the workshop were huge successes attracting 100+ AI researchers to discuss a variety of topics. DEEP-DIAL 21 will have reviewed paper presentations, invited talks, panels, and open contributions of datasets and chatbots. Accepted papers will be preferentially considered for Frontiers Journal's Open Access Special Issue on Collaborative Assistants for Society.
For DEEP-DIAL 2021, topics of Interest Include:
Collaborative Assistants and Health, especially COVID-19
Dialog and Finance Industry
Assistants for Education, especially Distant Education
Design: Dialog Systems
Design considerations for dialog systems
Evaluation of dialog systems, metrics
Open domain dialog and chat systems
Style, voice and personality in spoken dialogue and written text
Novel Methods for NL Generation for dialogs
Early experiences with implemented dialog systems
Mixed-initiative dialogs where a partner is a combination of agent and human
Domain model acquisition, especially from unstructured text
Plan recognition in natural conversation
Planning and reasoning in the context of dialog systems
Optimal dialog strategies
Learning to reason
Learning for dialog management
End2end models for conversation
Explaining dialog policy
Ethical issues with learning and reasoning in dialog systems
Corpora, Tools and Methodology for Dialogue Systems
Securing one’s chat
The intended audience students, academic researchers and practitioners with an industrial background from the AI sub-areas of dialog systems, learning, reasoning, planning, HCI, ethics and knowledge representation.