The purpose of this paper is to propose a NeuralQ_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_lear...

This paper proposes a behavior-based scheme for high-level control of autonomous robots. Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories in cooperative ones. As a second feature, behavior state/acti...

Learners such as humans and intelligent agents, often require support to perform complex tasks in real world environments. Inaccessible states and the complexity of tasks add to this requirement. Large state and action spaces associated with the environments also contribute to this need for support. In this paper, we present a design of a learning agent that learns from the environment in order...

Coping with rapid changes in technologies in professional lives requires tools that can persistently train the users. An important task for humans is to control the physical system behaviors with prediction. Though humans learn to perform this task with relative ease over several natural physical systems, engineered physical systems pose a problem as they are often inaccessible for natural inte...

Nowadays, skin cancer is one of the most important problems faced by world, due especially to rapid development cells and excessive exposure UV rays. Therefore, early detection at an stage employing advanced automated systems based on AI algorithms plays a major job in order effectively identifying detecting disease, reducing patient health financial burdens, stopping its spread skin. In this c...

In a robotic soccer team, goalkeeper is an important challenging role, which has different characteristics from the other teammates. This paper proposes a new learning-based behavior model for a soccer goalkeeper robot by using Petri nets. The model focuses on modeling and analyzing, both qualitatively and quantitatively, for the goalkeeper role so that we have a model-based knowledge of the ta...

The use of renewable energy in power generation and sudden changes in load and fault in power transmission lines  may cause a voltage drop in the system and challenge the reliability of the system. One way to compensate the changing nature of renewable energies in the short term without the need to disconnect loads or turn on other plants, is the use of renewable energy storage. The use of ener...