Modeling characters that interact with users as part of a character-as-a-service implementation

A character engine that executes on one or more processors, the character engine comprising:

• a user intent engine that, when executed by the one or more processors, evaluates user input data that is associated with a user device to determine a user intent;
• a domain engine that, when executed by the one or more processors, evaluates at least one of the user input data or the user intent to identify an assessment domain;
• and
• an inference engine that, when executed by the one or more processors:
• selects at least one inference algorithm from a plurality of inference algorithms based on the user intent and the assessment domain, wherein each inference algorithm included in the plurality of inference algorithms implements machine learning functionality;
• generates an inference based on the at least one inference algorithm;
• selects a first set of personality characteristics and a second set of personality characteristics from a plurality of sets of personality characteristics based, at least in part, on the inference, wherein the first set of personality characteristics is selected for generating content of a character response and the second set of personality characteristics is selected for generating an expression of the content of the character response, wherein the first set of personality characteristics comprises a first plurality of parameters and the second set of personality characteristics comprises a second plurality of parameters that is different from the first plurality of parameters, each parameter being associated with a personality dimension;
• and
• compute the character response to the user input data based on the at least one inference algorithm, the user input data, the first set of personality characteristics, the second set of personality characteristics, and data representing knowledge associated with a character;
• and
• an output device abstraction infrastructure that, when executed by the one or more processors, causes the user device to output the character response to a user.

One or more non-transitory computer-readable media including instructions that, when executed by one or more processors, cause the one or more processors to generate a character response during an interaction with a user by performing the steps of:

• evaluating user input data that is associated with a user device to identify a user intent and an assessment domain;
• selecting at least one inference algorithm from a plurality of inference algorithms based, at least in part, on the user intent and the assessment domain, wherein each inference algorithm included in the plurality of inference algorithms implements machine learning functionality;
• causing the at least one inference algorithm to compute an inference based on the user input data and data representing knowledge associated with a character;
• selecting a first set of personality characteristics and a second set of personality characteristics from a plurality of sets of personality characteristics based, at least in part, on the inference, wherein the first set of personality characteristics is selected for generating content of the character response and the second set of personality characteristics is selected for generating an expression of the content of the character response, wherein the first set of personality characteristics comprises a first plurality of parameters and the second set of personality characteristics comprises a second plurality of parameters that is different from the first plurality of parameters, each parameter being associated with a personality dimension;
• and
• causing a personality engine associated with the character to compute the character response to the user input data based on the inference, the first set of personality characteristics, and the second set of personality characteristics.