2022/09/12 by Yaniv Oshrat, Oshrat, Yaniv, Yonatan Aumann +11 · 1 citation
Psychology · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Human-Automation Interaction and Safety
paper · pdf · doi:10.48550/arxiv.2209.05226
openalex publication_date 2022/09/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The prospect of combining human operators and virtual agents (bots) into an effective hybrid system that provides proper customer service to clients is promising yet challenging. The hybrid system decreases the customers' frustration when bots are unable to provide appropriate service and increases their satisfaction when they prefer to interact with human operators. Furthermore, we show that it is possible to decrease the cost and efforts of building and maintaining such virtual agents by enabling the virtual agent to incrementally learn from the human operators. We employ queuing theory to identify the key parameters that govern the behavior and efficiency of such hybrid systems and determine the main parameters that should be optimized in order to improve the service. We formally prove, and demonstrate in extensive simulations and in a user study, that with the proper choice of parameters, such hybrid systems are able to increase the number of served clients while simultaneously decreasing their expected waiting time and increasing satisfaction.