Abstract: Disclosed herein are embodiments for managing a task including one or more skills. A server stores a virtual environment, software agents configured to collect data generated when a user interacts with the virtual environment to perform the task, and a predictive machine learning model. The server generates virtual entities during the performance of the task, and executes the predictive machine learning model to configure the virtual entities based upon data generated when the user interacts with the virtual environment. The server generates the virtual environment and the virtual entities configured for interaction with the user during display by the client device, and receives the data collected by the software agents. The system displays a user interface at the client device to indicate a measurement of each of the skills during performance of the task. The server trains the predictive machine learning model using this measurement of skills during task performance.

Abstract: Disclosed herein are embodiments for managing a task including one or more skills. A server stores a virtual environment, software agents configured to collect data generated when a user interacts with the virtual environment to perform the task, and a predictive machine learning model. The server generates virtual entities during the performance of the task, and executes the predictive machine learning model to configure the virtual entities based upon data generated when the user interacts with the virtual environment. The server generates the virtual environment and the virtual entities configured for interaction with the user during display by the client device, and receives the data collected by the software agents. The system displays a user interface at the client device to indicate a measurement of each of the skills during performance of the task. The server trains the predictive machine learning model using this measurement of skills during task performance.

Abstract: Various embodiments described herein relate to a server-based virtual training environment monitor, which may configure and customize an exercise and fitness program accessible through augmented and virtual reality applications running on an electronic device of a user, based on a current state and events associated with the user. The current state and events are determined through reactive agents (for example, intelligent agents) and monitoring devices (for example, sensors), which are directly or indirectly associated with the electronic device.

Abstract: Disclosed herein are embodiments for managing a task including one or more skills. A server stores a virtual environment, software agents configured to collect data generated when a user interacts with the virtual environment to perform the task, and a predictive machine learning model. The server generates virtual entities during the performance of the task, and executes the predictive machine learning model to configure the virtual entities based upon data generated when the user interacts with the virtual environment. The server generates the virtual environment and the virtual entities configured for interaction with the user during display by the client device, and receives the data collected by the software agents. The system displays a user interface at the client device to indicate a measurement of each of the skills during performance of the task. The server trains the predictive machine learning model using this measurement of skills during task performance.

Abstract: The methods and systems disclosed herein generally relate to automated execution and evaluation of computer network training exercises, such as in a virtual environment. A server generates a training system having a virtual attack machine and a virtual target machine where the virtual target machine is operatively controlled by a trainee computer. The server then executes a simulated cyber-attack and monitors/collects actions and responses by the trainee. The server then executes an artificial intelligence model to evaluate the trainee's action and to identify a subsequent simulated cyber-attack (e.g., a next step to the simulated cyber-attack). The server may then train the artificial intelligence model using various machine-learning techniques using the collected data during the exercise.

Abstract: An example method includes storing a scenario event list that defines one or more events associated with a training exercise, and configuring, based on the events defined in the scenario event list, one or more software agents to emulate one or more cyber-attacks against a host computing system during the training exercise, which includes configuring the software agents to save a state of one or more resources of the host computing system prior to emulating the cyber-attacks and to restore the state of the resources upon conclusion of the cyber-attacks. The example method further includes deploying the software agents for execution on the host computing system during the training exercise to emulate the cyber-attacks against the host computing system using one or more operational networks.

Abstract: An example method includes deploying, by a modular training system and on one or more virtual machines in a network, one or more training environments that are configured to execute one or more training exercises; deploying, by the modular training system and for execution by one or more remote host computing systems that are communicatively coupled to the network, one or more software agents that are executed during the one or more training exercises, wherein the one or more software agents are configured to collect parameter data from the one or more remote host computing systems while the one or more trainees perform actions during the training exercise; and receiving, by the modular training system and from the one or more remote host computing system via the network, the parameter data collected by the one or more software agents during execution of the one or more training exercises.

Abstract: An example method includes storing a scenario event list that defines one or more events associated with a training exercise, and configuring, based on the events defined in the scenario event list, one or more software agents to emulate one or more cyber-attacks against a host computing system during the training exercise, which includes configuring the software agents to save a state of one or more resources of the host computing system prior to emulating the cyber-attacks and to restore the state of the resources upon conclusion of the cyber-attacks. The example method further includes deploying the software agents for execution on the host computing system during the training exercise to emulate the cyber-attacks against the host computing system using one or more operational networks.