Integrating Ontologies and Cognitive Conversational Agents in On2Conv

Multiagent systems have been successfully used in many domains. Being social, they are expected to communicate with human users in natural language. Nevertheless, the natural interaction between agents and humans is still challenging. Chatbot technologies are a key enabler to boost the communication between humans and software agents, but few technical solutions exist that make the agents’ reasoning capabilities easily accessible by a human user via a chatbot and, on the other hand, the chatbot’s answers more controllable and explainable. Dial4JaCa is one of such tools. It creates a bridge between Dialogflow and the JaCaMo cognitive-oriented and symbolic AI-based framework: the user’s interface is a Dialogflow chatbot allowing the user to interact in natural language, and the backend implementing the reasoning and performing required actions is a JaCaMo agent. However, in Dial4JaCa the consistency between data that feed the JaCaMo agent and those that feed the Dialogflow chatbot must be guaranteed by the developer via an error-prone and tedious manual process. By taking an ontology describing the domain of interest in input and generating both the skeleton for the JaCaMo agent’s behaviour and the intents for the Dialogflow chatbot, On2Conv improves Dial4JaCa robustness and reliability, and moves one step towards an explainable integration of agents and chatbots.