What comes closest to human thought represented in a computer are the so-called neural networks belonging to the branch of artificial intelligence. The problem is that a computer or algorithm does not have the same capacity as a brain to link data so quickly and efficiently. Professor Yusniel Hidalgo is working with that through data linked by RDF graphs.

I agree with Estaban Blanco Camargo en la proximidad del about the proximimity of the neural networks to some processes in the human brain. But there are much more examples. By example, the Selection of Proposals method imitate de behaviour of the human beings preparing and maing decisions in adeministrative fam,ilar and other meetings. But this procedure take place in the brain solving probles: divide s the problem in subproblems, generate solutions populations and searchy the best for the whole system smfor each subproblemsolutions co mposition of the received proposals. In general the human beings transfer the processes in its brain to the social and duresthat work inlife the scientific workto ., elaborated by me,sthek, humanmtoes s

Potentially of interest: https://books.google.fi/books/about/Integrating_Rules_and_Connectionism_for.html?id=P5FQAAAAMAAJ

This topic seems very important to me, and from what I was investigating this is because artificial intelligence, also called computational intelligence, is the intelligence exhibited by intelligent machines that is a flexible rational agent that perceives its environment and carries out actions that Maximize your chances of success in some goal or task. It applies when a machine imitates the "cognitive" functions that humans associate with other human minds, such as: "learn" and "solve problems." As machines become increasingly capable, technology that was once thought to require intelligence is removed from definition.

I have never been impressed by people who predict that one day AI will reach the level of the human brain. To me it shows a severe lack of understanding of how the human brain functions. There are many examples to show that though AI can imitate some aspect of human brain function, it can never replicate the human brain completely. A simple example will perhaps show the unbridgeable gap between AI and the human brain. AI is based on symbolic logic and binary number system. All the circuits in the AI work on this basic premise. However, though the human brain does use the AI way of thinking to solve problems, such as to build AI machines, it is only one of many repertoires available to the brain. We have no idea how many kinds or ways of thinking the brain has or is capable of having when confronted by a problem or a situation that needs to be addressed. The brain can look at gravity as a force with instantaneous action at a distance, as a field that surrounds the generating source or as a warping of the void that is surrounding an object. It can look at all of these three ways simultaneously as well as separately. thanks.

One of the main reason is because the human behavior is not standart for all of as. It means that the rassonable for one could be stupid for an other. How to formalize this ? ,to be included into a model.

each person is different so everyone sees things in a different way and has their own reasoning and however advanced this technology is always going to depend on human reasoning for its development

The human mind has an innate or acquired logical structure due to its interaction with its environment. The properties of the human mind have been selected in our ancestors and transmitted by inheritance to us. There are different types of computation that are approximate simulations of different processes of the mind: classical symbolic computation, networks of neurons artificial, genetic algorithms, fuzzy logic, dynamic systems. The networks of artificial neurons were created to simulate the creative activity of the mind, supporting itself at all times of the cerebral functioning. The system can change its weights and its connections and, thus, simulate the learning. The networks simulate well the development of the perceptual categorization. , but not the higher activities (for example, conceptualization). Making the modeling of brain activity in computers more and more difficult.

Each person is different and unique, only patterns are governed to try to model human behavior in a computer, which may already be real enough, with the great difference that computers have no feelings and are not able to identify any event Specifically, although every day we are getting closer and closer to achieving this

Of course, human reasoning is always going to be more difficult to introduce into a computer and that each person has a way of seeing things, so for some people it's fun for other things to be boring. And as Sindia rightly said, the technology to be able to develop needs human knowledge

I consider that the reasoning of a person is the most difficult that can be represented in a computer because the computer is based on algorithms and people have feelings and emotions that can not be represented with algorithms. Also each person is different and unique in the world.

This topic seems very important to me, because artificial intelligence is the intelligence exhibited by intelligent machines that is a flexible rational agent that perceives its environment and carries out actions that maximize its possibilities. of success in some objective or task. It is applied when a machine imitates the "cognitive" functions that humans associate with other human minds, such as: "learn" and "solve problems". As machines become increasingly capable, the technology that was once thought to require intelligence was removed from the definition.