Chat Failures and Troubles: Reasons and Solutions

TL;DR

This paper analyzes common failure causes in human-robot chat interactions and proposes solutions like closed-loop control, online learning, and reinforcement learning to improve AI chat performance.

Contribution

It introduces a comprehensive framework for diagnosing chat failures and suggests specific AI training and control strategies for continuous improvement.

Findings

Identified key causes of chat failures in HRI.

Proposed closed-loop control and online learning methods.

Recommended reinforcement learning for self-updating models.

Abstract

This paper examines some common problems in Human-Robot Interaction (HRI) causing failures and troubles in Chat. A given use case's design decisions start with the suitable robot, the suitable chatting model, identifying common problems that cause failures, identifying potential solutions, and planning continuous improvement. In conclusion, it is recommended to use a closed-loop control algorithm that guides the use of trained Artificial Intelligence (AI) pre-trained models and provides vocabulary filtering, re-train batched models on new datasets, learn online from data streams, and/or use reinforcement learning models to self-update the trained models and reduce errors.