Abstract: Computer-implemented systems and methods update rules engines in a distributed computer system with new rules in a lightweight, non-intrusive, real-time manner. Rules engines are subscribed to a pub/sub service for new rules pertaining to a topic. A rules manager publishes a new rule to the pub/sub service with an associated topic. The rules engines download the new rule and store the new rule in-memory for execution without downtime.

Abstract: A controller for controlling an entity is provided. The controller comprises a memory to store a hierarchical multimodal reinforcement learning (RL) neural network, and a processor. The hierarchical multimodal RL neural network includes a first level controller and two second level controllers. Each of the second level controllers comprise a first sub level controller relating to a first modality and a second sub level controller relating to a second modality. The first modality is different from the second modality. The processor is configured to select one of the two second level controllers to perform a first sub-task relating to a task, using the first level controller, based on input data and a state of the hierarchical multimodal RL neural network. The selected second level controller is configured to determine a set of control actions to perform the first sub-task, and control the entity based on the set of control actions.