On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments
This is an incremental position paper proposing chatbots as a platform for studying autonomy in dynamic settings, relevant to researchers and developers in conversational AI.
The paper argues that chatbots in dynamic environments can serve as a research platform for goal-directed autonomy and handle business applications, demonstrated through Water Advisor, a system that accesses and explains water quality data.
Conversation interfaces (CIs), or chatbots, are a popular form of intelligent agents that engage humans in task-oriented or informal conversation. In this position paper and demonstration, we argue that chatbots working in dynamic environments, like with sensor data, can not only serve as a promising platform to research issues at the intersection of learning, reasoning, representation and execution for goal-directed autonomy; but also handle non-trivial business applications. We explore the underlying issues in the context of Water Advisor, a preliminary multi-modal conversation system that can access and explain water quality data.