Abstract: A processor may receive data associated with a user. The processor may determine, using an artificial intelligence model, a contextual situation the user is likely to encounter. The processor may identify, using the artificial intelligence model, a task that the user is likely to perform in the contextual situation. The processor may determine, using the artificial intelligence model, a criticality of the task the user is likely to perform in the contextual situation. The processor may generate a simulation of the task in a virtual reality simulation. The processor may prompt the user to utilize the task simulation to learn how to perform the task.

Abstract: A computer-implemented method for determining contextual relevance in multi-auditory source scenarios is disclosed, the method including receiving, by a cognitive system, auditory communications regarding a current activity, analyzing, by the cognitive system, each auditory communication to determine an intended action. For each intended action, the cognitive system creates a simulation to identify a resulting outcome of each intended action. The method further includes ranking, by the cognitive system, the resulting outcome, the ranking based on a comparison of each simulated result and the corresponding intended action regarding the current activity, and physically implementing the highest rated resulting outcome(s) for the current activity. The analyzing, in one example, includes assigning a weight to each of the relevant auditory communications based on one or more criterion, and ranking the relevant auditory communications by weight.

Abstract: A computer-implemented method for determining contextual relevance in multi-auditory source scenarios is disclosed, the method including receiving, by a cognitive system, auditory communications regarding a current activity, analyzing, by the cognitive system, each auditory communication to determine an intended action. For each intended action, the cognitive system creates a simulation to identify a resulting outcome of each intended action. The method further includes ranking, by the cognitive system, the resulting outcome, the ranking based on a comparison of each simulated result and the corresponding intended action regarding the current activity, and physically implementing the highest rated resulting outcome(s) for the current activity. The analyzing, in one example, includes assigning a weight to each of the relevant auditory communications based on one or more criterion, and ranking the relevant auditory communications by weight.

Abstract: A computer-implemented method for determining contextual relevance in multi-auditory source scenarios is disclosed, the method including receiving, by a cognitive system, auditory communications regarding a current activity, analyzing, by the cognitive system, each auditory communication to determine an intended action. For each intended action, the cognitive system creates a simulation to identify a resulting outcome of each intended action. The method further includes ranking, by the cognitive system, the resulting outcome, the ranking based on a comparison of each simulated result and the corresponding intended action regarding the current activity, and physically implementing the highest rated resulting outcome(s) for the current activity. The analyzing, in one example, includes assigning a weight to each of the relevant auditory communications based on one or more criterion, and ranking the relevant auditory communications by weight.