Federated Learning in Robotic and Autonomous Systems

Machine Learning for Autonomous Robotic Agents

We present some results of our research in the field of Machine Learning applied to robotics problems. In particular we have investigated on: (i) the application of Learning Classifier Systems to the synthesis of robot controllers; (ii) learning of fuzzy controllers; (iii) learning of purposeful representations of the environment; (iv) and the application of versions of Q-learning to robot trai...

TAROS 2007: Towards Autonomous Robotic Systems.

SAMON: Communication, Cooperation and Learning of Mobile Autonomous Robotic Agents

The Applied Research Laboratory Penn State University “Ocean SAmpling MObile Network” (SAMON) Project is developing the simulation testbed for the oceanographic communities interactions through the Web interface and the simulation based design of Autonomous Ocean Sampling Program missions. In this paper, a current implementation of the SAMON is presented, and a formal model based on interactive...

Planning, Learning, and Executing in Autonomous Systems

Abs t rac t . Systems that act autonomously in the environment have to be able to integrate three basic behaviors: planning, execution, and learning. Planning involves describing a set of actions that will allow the autonomous system to achieve high utility (a similar concept to goals in high-level classical planning) in an unknown world. Execution deals with the interaction with the environmen...

Self-Organizing Maps with Eligibility Traces: Unsupervised Control-Learning in Autonomous Robotic Systems

This paper presents the application of a connectionist control-learning system to autonomous mini-robots. These robots are specially designed and equipped for learning easily deened yet challenging control tasks. The system must learn despite noisy, low-grain sensory input and uncertain interactions between motor commands and eeects in the world. The system's design is severely constrained by t...