— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
Abstract--Acquisition of new sensorimotor knowledge by imitation is a promising paradigm for robot learning. To be effective, action learning should not be limited to direct replic...
Abstract— Teams of mobile robots have been recently proposed as effective means of completing complex missions involving multiple tasks spatially distributed over a large area. A...
Alejandro R. Mosteo, Luis Montano, Michail G. Lago...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
We apply evolutionary algorithm (EA) to the design of controller for adaptive robots. EAs can be successful for more complicated tasks, where traditional engineering methods strugg...