A Neural Conversational Model

This paper introduces a neural network approach to building conversational agents. It uses a sequence-to-sequence model to predict the next sentence in a conversation, learning from a large dataset of dialogues. The model demonstrates the ability to generate meaningful responses and capture some aspects of conversation, laying a foundation for more advanced conversational AI systems.