Intelligent robotic agent combining reactive and cognitive capabilities

We present the concept of an intelligent robotic agent that displays both learning-based and reactive capabilities. The learning-based components of the agent enable it to build up action strategies over its lifetime in a real world environment. Due to its complexity and dynamically changing nature, it is impossible to gather full knowledge about the environment. This necessitates the addition of reactive components that enable the robotic agent to carry out tasks in the presence of environment uncertainties. Our view of an intelligent robotic agent is based on the decomposition into a learning-based action planner and a reactive action executor part. We present an overview of the modules that implement the functionality of these two main components.