Selecting a response in a multi-turn interaction between a user and a conversational bot

A method for imitating a human conversational response, comprising:

• in association with an automated bot executing in a computing system:
• receiving a data model associated with a conversation, the data model comprising an observation history, together with a set of events;
• querying against a set of annotated conversations to generate a first set of one or more candidate interpretations for an input that is an utterance or action, wherein a candidate interpretation is a reference to a specific utterance or action in the set of annotated conversations that shares a same meaning as the input;
• for each candidate interpretation of the first set of candidate interpretations, creating an updated data model reflecting a new state of the conversation resulting from incorporating the candidate interpretation;
• coherency filtering the set of updated data models derived from the first set of candidate interpretations against one or more first tests of coherence to identify a particular updated data model, and persisting the particular updated data model as a current state of the conversation;
• using the particular updated data model, querying against the set of annotated conversations to generate a second set of one or more candidate interpretations for one or more observations that represent a possible response to the input;
• for each candidate interpretation of the second set of candidate interpretations, creating an updated data model reflecting a potential future state of the conversation resulting from appending the candidate interpretation;
• and
• coherency filtering the set of one or more updated data models derived from the second set of candidate interpretations against one or more second tests of coherence to identify a coherent response to the input for the automated conversational bot;
• the automated bot returning the coherent response to the input.