  Prior studies addressing target-oriented conversational tasks lack a crucial
notion that has been intensively studied in the context of goal-oriented
artificial intelligence agents, namely, planning. In this study, we propose the
task of Target-Guided Open-Domain Conversation Planning (TGCP) task to evaluate
whether neural conversational agents have goal-oriented conversation planning
abilities. Using the TGCP task, we investigate the conversation planning
abilities of existing retrieval models and recent strong generative models. The
experimental results reveal the challenges facing current technology.
