Generic command interpretation algorithms for conversational agents

International audienceThis paper focuses on the human-machine communication within the framework of intelligent agents. We propose a generic architecture provided with a natural language (NL) algorithm for command interpretation that can be adapted to different agent's domains. Our NL architecture only depends on the agent's code and its domain ontology. We consider two classical approaches for NL command interpretation: the top-down approach, which relies on the agent's model syntactical constraints, and the bottom-up approach which relies on the set of the agent's possible actions. We propose to combine both approaches in a bottom-up based algorithm that makes use of agent's constraints. We propose a comparative evaluation of these three algorithms

Generic command interpretation algorithms for conversational agents

International audienceThis paper focuses on human-machine communication with intelligent agents, it proposes a generic architecture with an algorithm for natural language (NL) command interpretation which makes it easy to define different applications using the description and domains of the different agents, since all that is required is their respective codes and domain ontologies. There are two classical approaches for NL command interpretation: the top-down approach, which relies on the syntactical constraints of the agent's model, and the bottom-up approach which relies on the set of the agent's possible actions. The present work combines the two in a new bottom-up based algorithm that makes use of agent's constraints. The three algorithms are then compared, and results show that the combined approach gives best results