Conversational question answering over a knowledge graph involves engaging in natural, dialogue-like interactions with a system that uses a knowledge graph to provide accurate and relevant answers. By leveraging the rich symbolic triplet information in the knowledge graph, the system can deliver precise answers during the conversation. In this chapter, we discuss how to use neural network-based reinforcement learning methods to answer conversational questions with the help of symbolic knowledge from the knowledge graph.