A method implemented by an autonomous personal companion embodied within a robot that is mobile, wherein the autonomous personal companion comprises an artificial intelligence engine configured to implement a local artificial intelligence model , and wherein the autonomous personal companion is located within the same physical environment as a user and provides services to the user, the method comprising: capturing data, related to the physical 2. environment and behavior of the user , using the autonomous personal companion ; analyzing the data to identify one or more patterns of user behavior in the data from a plurality of predefined patterns, wherein each of the plurality of predefined patterns is associated with a corresponding predefined tag, wherein the plurality of predefined patterns is generated from a deep learning engine in dependence upon data related to the physical environment and actions of the user; classifying the identified patterns as a collected set of tags, wherein tags in the collected set are associated with the one or more identified patterns; comparing the collected set of tags to each of a plurality of sets of predefined tags associated with a plurality of scenarios, wherein each scenario corresponds to one or more predefined patterns of user behavior and a corresponding set of predefined tags; assigning a weight to each of the sets of predefined tags based on the comparing, wherein each weight defines a corresponding match quality between the collected set of tags and a corresponding set of predefined tags; sorting the plurality of sets of predefined tags by corresponding weights in descending order; selecting a matched scenario to the collected set of tags, wherein the matched scenario is associated with a matched set of predefined tags having a corresponding weight with the highest match quality; providing the captured data as input into a matched algorithm of the matched scenario that is executed to determine a behavior associated with the personal companion; and performing one or more actions based on the determined behavior, wherein at least one action includes moving the robot. capturing data, related to the physical 2. environment and behavior of the user , using the autonomous personal companion ; analyzing the data to identify one or more patterns of user behavior in the data from a plurality of predefined patterns, wherein each of the plurality of predefined patterns is associated with a corresponding predefined tag, wherein the plurality of predefined patterns is generated from a deep learning engine in dependence upon data related to the physical environment and actions of the user; classifying the identified patterns as a collected set of tags, wherein tags in the collected set are associated with the one or more identified patterns; comparing the collected set of tags to each of a plurality of sets of predefined tags associated with a plurality of scenarios, wherein each scenario corresponds to one or more predefined patterns of user behavior and a corresponding set of predefined tags; assigning a weight to each of the sets of predefined tags based on the comparing, wherein each weight defines a corresponding match quality between the collected set of tags and a corresponding set of predefined tags; sorting the plurality of sets of predefined tags by corresponding weights in descending order; selecting a matched scenario to the collected set of tags, wherein the matched scenario is associated with a matched set of predefined tags having a corresponding weight with the highest match quality; providing the captured data as input into a matched algorithm of the matched scenario that is executed to determine a behavior associated with the personal companion; and performing one or more actions based on the determined behavior, wherein at least one action includes moving the robot. <EOS>