A narrative relies on the imperfect knowledge of the user to create interactions between the characters that are ultimately used as a plot device to drive the narrative. This motivates our exploration of ways to encode this information, provides means for a user to both query and influence the knowledge, and guides the user based on a model of their experience. We developed PICA: a proactive intelligent conversational agent for interactive narratives that can guide users through such experiences. The underlying knowledge base is designed using a sub-symbolic architecture, which encodes belief models for multiple users and autonomous agents in addition to the actual story knowledge. We also developed a discourse module using Behavior Trees to intuitively design the proactive and reactive capabilities of PICA. We compare our approach to neural networks and symbolic knowledge bases and demonstrate its functionality.