This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …

Due to the significance and value in human-computer interaction and natural language
processing, task-oriented dialog systems are attracting more and more attention in both …

A conversational information retrieval (CIR) system is an information retrieval (IR) system
with a conversational interface, which allows users to interact with the system to seek …

Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence
(AI) by endowing autonomous systems with high levels of understanding of the real world …

Dialog policy decides what and how a task-oriented dialog system will respond, and plays a
vital role in delivering effective conversations. Many studies apply Reinforcement Learning …

Trainable chatbots that exhibit fluent and human-like conversations remain a big challenge
in artificial intelligence. Deep Reinforcement Learning (DRL) is promising for addressing this …

The potential for conversational agents offering mental health and legal counseling in an
autonomous, interactive, and vitally accessible environment is getting highlighted due to the …

Dialogue policy learning (DPL) is a key component in a task-oriented dialogue (TOD)
system. Its goal is to decide the next action of the dialogue system, given the dialogue state …

User Simulators are one of the major tools that enable offline training of task-oriented
dialogue systems. For this task the Agenda-Based User Simulator (ABUS) is often used. The …

The shortage of therapists for mental health patients emphasizes the importance of globally
accessible dialogue systems alleviating their issues. To have effective interpersonal …