This paper discusses how a robot can develop its state vector according to the complexity of the interactions with its environment. A method for controlling the complexity is prop...
In this paper, we introduce a new technique for modeling and solving the dynamic power management (DPM) problem for systems with complex behavioral characteristics such as concurr...
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Abstract--The particle swarm is an algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. Even though t...
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...