Abstract: This specification provides a computer-implemented method comprising providing, by a user, one or more demonstrations of a video game entity interacting with a video game environment to achieve a goal. The method further comprises generating, from the one or more demonstrations, one or more training examples. The method further comprises training an agent to control the video game entity using a neural network. The training comprises generating one or more predicted actions for each training example by processing, using the neural network, input data derived from the training example, and updating parameters of the neural network based on a comparison between the one or more predicted actions of the training examples and the one or more corresponding target actions of the training examples. The method further comprises performing validation of the video game environment, comprising controlling the video game entity in the video game environment using the trained agent.

Abstract: Systems and methods of curiosity driven reinforcement learning agents promote novel exploration of a virtual interactive environment. The data of the exploration can be stored in a buffer to determine, generate, and display visualizations in the virtual interactive environment. The visualizations can correspond to identify issues in the virtual interactive environment and/or identify relationships between regions of the virtual interactive environment.

Abstract: Systems and methods of curiosity driven reinforcement learning agents promote novel exploration of a virtual interactive environment. The data of the exploration can be stored in a buffer to determine, generate, and display visualizations in the virtual interactive environment. The visualizations can correspond to identify issues in the virtual interactive environment and/or identify relationships between regions of the virtual interactive environment.