Ravel : A MAS orchestration platform for Human-Chatbots Conversations

This paper presents Ravel, a multiagent systems (MAS) platform aimed to integrate natural language understanding components with orchestration components of dialogues between human beings and agents. Ravel enables the specification of (social) conversations norms, using deontic logic, for use in contexts where multiple agents and human users are conversing in natural language. We demonstrate the usefulness and versatility of Ravel in a chat-based finance adviser system designed as a chat group of five participants: four collaborative chatbots with two different roles (mediator and expert) and a human or chatbot user.