Many expert systems have been developed for self-adaptive PID controllers of mobile robots. However, the high computational requirements of the expert systems layers, developed for the tuning of the PID controllers, still ...

The widespread use of virtual learning environment (VLE) has great potential for the development of applications that meet needs in education. U -Learning environments the goal is to seek information related to the needs ...

This paper presents the computation of feasible paths for mobile robots in known and unknown environments using a QAPF learning algorithm. Q-learning is a reinforcement learning algorithm that has increased in popularity ...

On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the ...

The aim of this paper is to develop an AI agent with self-learning capabilities that is able to play classical Atari console games without human intervention and achieve next to human level performance. In order to achieve ...

Reinforcement Learning (RL) is a machine learning paradigm wherein an artificial agentinteracts with an environment with the purpose of learning behaviour that maximizesthe expected cumulative reward it receives from the ...

Techniques of optimization known as metaheuristics have achieved success in the resolution of many problems classified as NP-Hard. These methods use non deterministic approaches that reach very good solutions which, however, ...