Many areas in power systems require solving one or more nonlinear optimization problems.
While analytical methods might suffer from slow convergence and the curse of …

For a swarm of mobile robots in an unknown environment, the most challenging task is to
plan the optimal path and also to learn the environmental parameters. Machine learning is …

In this paper, we treat optimization problems as a kind of reinforcement learning problems
regarding an optimization procedure for searching an optimal solution as a reinforcement …

Particle swarm optimization (PSO) and differential evolution (DE) have their similarities and
compatibility in the design update process, such that a new design vector is determined by …

Wireless Sensor Networks (WSN) have emerged as a key technology with a wide range of
possible applications. In routing methods that are specifically intended for wireless sensor …

Classical Q-learning algorithm is a reinforcement of learning algorithm that has been
applied in path planning of mobile robots. However, classical Q-learning suffers from slow …

Sistemas multiagentes têm sido um foco importante de pesquisas para diversas aplicações
desde a robótica com robôs interagindo e competindo entre si ou em jogos em que diversos …