An artificial neuron network is an organized group of interconnected artificial neurons, which conduct sophisticated operations or find a solution for complex problems with the help of a type of learning based on a form of artificial intelligence (AI).
An artificial neuron represents a basic unit of treatment of an artificial neural network —inspired by the biological neural network. This neuron converts the information-carrying signals it receives into a signal that it sends to other units in the network or to the output.
Reinforcement learning allows the computer to learn what to do from repeated experiences where it must find the best solution. In other words, he learns by trial and error, receiving or not a digital reward after each action.
Machine learning is a process by which a computer or software improves, without human intervention, its mode of operation by acquiring new knowledge and skills from the results it has obtained during previous actions.
Cognitive sciences gather disciplines that aim to describe and explain the mechanism of human, animal and artificial thought, and every complex system of information processing able to acquire, retain, use and transmit knowledge.
Artificial intelligence (AI) refers to the set of theories and technologies used to develop machines or software capable of simulating cognitive functions associated with human intelligence, such as learning or reasoning.