System and method thereof for automatically updating a decision-making model of an electronic social agent by actively collecting at least a user response

A non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry for updating a decision-making model of an electronic social agent by actively collecting at least a user response, the process comprising:

• receiving an indication of an action that has been performed by the electronic social agent;
• collecting in near real-time at least a portion of a first dataset and at least a first user response with respect to the performed action, wherein the first dataset indicates at least a current state;
• applying at least one algorithm, wherein the at least one algorithm is a machine learning (ML) algorithm, to determine, based on the first dataset and the first user response, whether collection of at least a second user response is desirable;
• generating a question for collecting the at least a second user response;
• determining an optimal time for presenting the at least a question to the user;
• presenting, by the electronic social agent, the at least a question to the user at the determined optimal time;
• collecting, using at least one sensor the at least a second user response;
• and
• updating the decision-making model of the electronic social agent based on the collected at least a second user response.

A system for updating a decision-making model of an electronic social agent by actively collecting at least a user response, comprising:

• a processing circuitry;
• and
• a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:
• receive an indication of an action that has been performed by the electronic social agent;
• collect in near real-time at least a portion of a first dataset and at least a first user response with respect to the performed action, wherein the first dataset indicates at least a current state;
• apply at least one algorithm, wherein the at least one algorithm is a machine learning (ML) algorithm, to determine, based on the first dataset and the first user response, whether collection of at least a second user response is desirable;
• generate a question for collecting the at least a second user response;
• determining an optimal time for presenting the at least a question to the user;
• present, by the electronic social agent, the at least a question to the user at the determined optimal time;
• collect, using at least one sensor the at least a second user response;
• and
• update the decision-making model of the electronic social agent based on the collected at least a second user response.