TRAINING OF CONVERSATIONAL AGENT USING NATURAL LANGUAGE

Aspects of the present disclosure relate to training a conversational agent. A conversational agent is initiated with a set of atomic operators, each atomic operator having one or more atomic operator rules for executing operations. A natural language input is received from a user on a conversational interface. A determination is made whether the natural language input maps to an existing script by referencing a rules engine. In response to a determination that the natural language does not map to an existing script, training is requested from the user. Training is then received from the user which maps the natural language input to a script. A mapping rule which maps the natural language input to the script is stored, and the script is executed.