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Prolog Primer: Declarative Programming

Introduction:
In the early 70's French language developed Alain Colmenuer Prolog also allows the development of applications in a declarative way.

PROLOG In general the automatic is a problem demonstrator, which uses a Knowledge Base in the form of deductive inference rules (Horn clauses), ie, its rules have resulted in a single action and the inferences obtained ned strictly logical (true or false), although it may seem a limitation, it does not is entirely fair, since PROLOG allows logic programming with probabilistic inference mechanisms, since it is searching trees with accumulation of evidence.

The PROLOG as a language of predicate calculus emerged, took the following ideas of logic for implementation.
1) A set of axioms or facts.
2) Rules of inference which are solved by resolution and unification.
3) The objective to demonstrate the conditions that will unify the rules. LISP
also took the treatment of the lists for the representation of the Prolog complejas.Aunque structures had their origin in mathematical logic was not an exact transposition, and is linked to the discussions that hold the key for years Artificial Intelligence researchers, which are divided into two groups, firstly Minsky who proposes to study the mechanisms of human thought and then simulate on the computer.
Minsky The most important are the concepts, that is the interpretation that can be given to each word depending on a given context.

The other group headed by Mac Carthy (author of LISP), states that mathematical logic is the characteristic feature for the representation of reasoning and its implementation in the computer, this group focuses on the formalization and structure of knowledge rather than the sense of them.

since ancient logic was conceived as a method of discovering the laws of thought, but these laws have always been restricted to scientific thought and especially the mathematician, leaving out common sense. This deficiency is supported by advocates logic, but they consider that logic is the only way possible to develop programs capable of showing intelligence.


Declarative programming Declarative programming
The main thing is not the instructions given in sequence (programming prescriptive), instead, the programmer focuses on describing the problem through rules and facts that operate independently and it is through a mechanism of inference rules are implemented.

declarative programming in the rules (knowledge base) is separated from the control program (inference machine).

declarative programming Example:
If and / or and / or .... then and / or ....

Where a serious fact: John is a student

The dog is white
Maria loves movies.

operational knowledge is procedural in nature. Conclusion If premises then

(There are also those who use: If conditions then Actions)


If P then C Where: P and C instructions would be in the presence of a procedural representation. P and C
facts or assertions would be in the presence of a declarative representation. Example

procedural representation
If A1 = B1 and A2> B2 then X: = A1 + A2
Where
A1 = B1 and A2> B2 are comparisons to take real ¨ value, "or" false ¨.


So we have:

If P1 and P2 then C

where P1 and P2 would be logical variables (true or false would)

Example
If declarative representation and then

This in any language would be as follows:
X: = "John is a student"
Y: = "John has 7 years"

if X = "John is a student" and Y = "John has 7 years" Then Z
: = "John is in the primary"

Let's see how to formalize the facts or assertions
Example: John has 10 years of age
1)
<10>
2) relation (concept, a concept that uses Prolog's ,....)
age (John, 10) is also used

3)


We will concentrate on the first two performances.

Example 1: The lion is a mammal

is-a (lion, mammal)

Example 2: Mary likes movies.
1)
2) likes (maria, film)

Lets look at some examples where the facts are combined in the form of rules or clauses:

if and then


Now we formalize the facts:


1) if and then
Or

(similar to Prolog)
2) lives (shark, in-water) if he (fish, in-water) and is-a (swordfish, shark)

prolog Note that the conclusion stands in front of the premises

representation in the form of rules: if premises

Conclusion What then would be interpreted as if
then Where
conclusion can be made by several facts or assertions.

Representation in Prolog: Conclusion
if
Premises and be interpreted as if

Where the conclusion is given by a single fact or assertion.

Exercise 1:
1. Mary likes tennis.
2. Tommy likes baseball.
3. José likes sports likes Thomas.

1.
2. S
3. If so

Similar to prolog:
1. likes (maria, tennis)
2. like (footage, baseball)
3. like (Jose, X) If you like (sockets, X)

Exercise 2:

Sophie wants a man who does not smoke.

if and

Similar to prolog:
want (sofia, X) if man (X) and do not smoke (X)

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Towards a new approach to Artificial Intelligence

From the AI \u200b\u200bcrisis has created new areas of research IA such as
-
Neural Networks - Genetic Algorithms
- Distributed Artificial Intelligence

all have in common a new approach: intelligence is a product of the association, combination or connection of simpler independent entities (agents, genes or neurons) , which may have some and intelligence or any product of their interaction, the system would present an intelligent behavior. Which brings us to a new paradigm based on the copy of emerging systems and evolutionary nature, which in some ways is a return to the Cybernetics, the first technical science inspired by nature.

Research in the RNA have been immersed in building robots that learn to discover hidden relationships in data that can simultaneously encode and store information in a similar way as it does to the brain.

The Neurocomputation used as a basis the brain metaphor, but does not pursue the objective of building machines absolutely biologically plausible, but the development of useful machines.

intellectual capacity depends on the collective action of neurons that carry out processes in series and in parallel using feedback and a molecular and laminar organization with high capacity for self-organization and cooperativity based on a hierarchical structure that allows local processing centralized in phases.

Artificial Life is the name given to a new discipline was born in the 80, who studies the natural life by recreating biological phenomena in the computer and other artificial means, in order not only of theoretical understanding of phenomena under study, but also to discover and make practical and useful applications of biological principles in computer technology and engineering, for example, mobile robots, spacecraft, medicine, nanotechnology, industrial fabrication and assembly as well as other engineering projects.

In nature, evolution, particularly that of living beings, has certain characteristics that led to John Holland to start a research in an area that eventually became what today is called genetic algorithms (GA). The ability of a population of chromosomes to explore the search space "in parallel" and combine the best that it has been found through the mechanism of crossing-over (crossover), is intrinsic to the natural evolution and is being exploited by GAs.

From the biological standpoint, the problem centers on the imitation of the mechanism of evolution of living beings. Of a population are more likely to survive and have offspring those organisms best adapted to their environment. To combine two that have desirable characteristics for different aspects can arise both inherit new characteristics.

The premise of GAs, following the publication of the book of Holland "Adaptation in Natural and Artificial Systems "and the many researchers who use them as metaheuristic for optimization is that it can find approximate solutions to complex computational problems through a process of simulated evolution, in particular a mathematical algorithm implemented on a computer.

In Distributed Artificial Intelligence (DAI) studies collaborative problem solving by a group of distributed agents. Such cooperation is based on neither has the information (expertise, resources, etc) to fully resolve the problem and where an agent is characteristic of being a more or less autonomous entity with its own knowledge and environment and with the ability to interact with their environment and other agents.

Unlike expert systems, called by many "autistic systems" this new research dealing with that they are able to interact with the environment or what is like to be open and flexible.

Moreover, intelligent agents are emerging as one of the AI \u200b\u200bapplications more promising due to its close relation to the Internet (the third revolution in information). Without creating false expectations, we must remember the expert systems and intelligent agents given the advantages that account for network access. They are called to change our way of working to allow move users more comfortable and friendly environment. CONCLUSIONS




Until today, it is possible to develop systems that behave 'effective' in a specific subject, but not to 'emulate' human intelligence. The logic is only one edge of it: common sense, non-monotonic reasoning, recognition and other processes 'smart' are not yet fully resolved.

Chess programs are a tangible demonstration of what might be called an intelligence based on brute force, since their method is the computational speed, allowing you to search large areas and process a enormous amount of information processing speed that exceeds the human brain. Many believe that increasing the calculation speed of computers, which seems to have no limits, should lead to the emergence of so-called intelligent machines, a claim supported by the computers to be able to assess more variants of a problem, whether the game of chess , an estimate of engineering, industrial design or mechanical diagnosis, be able to achieve faster and more efficient solutions, relegating the human background. This argument is based on the accelerated growth that is evident in the computer hardware, while underestimating the development of software ignores the possibilities of the brain.

Today, science is no longer close in on herself and set in around him, understands that the best way to understand how something works in a human being is to understand first the simplest animals. So that science finds the emergent properties of intelligence, as a result of the complex interaction of simple elements and emulates the evolutionary genetic processes in the search for better solutions to really complex problems.


Artificial Intelligence 'conventional' in their attempts to mathematically model the processes of reasoning, could not achieve the dream of its creators, much less the IA followers called 'strong', those who have tried to convince us that thinking machines will be replaced. Begins a new era in Artificial Intelligence. The act of looking to nature will allow the man a step in the drive to achieve truly simulate human intelligence.

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crisis

As already mentioned, the first attempts at artificial intelligence (AI) were based on heuristic search. It is believed the man to solve all problems through heuristic and it was thought that the mind was made up of powerful heuristic devices capable of starting from the general to the particular as was the case with the algorithms computer. Hence the efforts to find a general algorithm based on heuristic principles that were able to solve any problem. One example was the GPS (general problem solver) with which one could prove any mathematical theorem, but was unable to solve problems of an elementary to require a minimum of common sense. This failure led researchers to conclude that the heuristic was not everything and that if the man solved the problem was because he possessed the necessary knowledge for solving.
.
What gave rise to the explosion of knowledge-based systems known as expert systems which due to its narrow domain of problem solving did not meet the expectations of users. This crisis resulted in the symbolist paradigm in AI paradigms which caused the most important being those based on connections and based on cooperation. As our recent interest because they are those related to cooperation between intelligent agents adjusting the model for the structure of an intelligent organization. Another

attempts of artificial intelligence was trying to understand mental states through "toy worlds", a product of lack of knowledge about the nature of intelligence and on the other hand, there was the belief that learning in these domains toy could be extended without difficulty to more complicated problems but because of the complexity of real world problems can not be captured in these reduced models and therefore must be raised directly. Crisis

AI: Artificial Intelligence

has always been seen as a theoretical science, disconnected from reality, while for others they are methods for investigating the brain. But really, what have been your achievements? How has influenced the understanding of the human mind?



The AI \u200b\u200bseemed to be irreconcilable if we analyze through its three branches:
- Study of the human mind.
- Intelligent computer systems.
- Commercial systems based on AI techniques

Study of the Mind: Discovering the mysteries of the human mind, where the machine is used as a laboratory to test theories.

computer systems: computer techniques to analyze the simulation of intelligent behavior

Commercial systems: the machine is a tool through smart programs will anyone in their daily tasks.

Each of these methods denies the other's progress, and in some cases considered that has nothing to do with Artificial Intelligence.

According to this approach there are three areas of research and development of Artificial Intelligence. Study

àCiencia cognitive mind.
computer systems to intelligent machines.
commercial system

Knowledge Engineering Study of the Mind:
is considered a natural science research on the mind trying to understand the mechanisms of human creativity rely on computers to support this group thought emerge two great ideas that have been filled with promises of AI research: strong AI and weak AI.

Strong Artificial Intelligence:
The idea of \u200b\u200bstrong AI has been the dream of almost all researchers in this field. Holds that all mental operations are manifestations of complex sophisticated computational processes, and that it is irrelevant whether such processes are carried out by a human subject, a physical object or an electronic device. It accepts that the human mind may be reproduced or copied to another medium, the brain is considered more support.


IA In exchange for the weak (less radical than the last, and most widespread since the collapse of the idealistic approach of the early years) is not aware computing, and artificial simulation mental activity in any case gives rise to mental phenomena such as pain, recognition, understanding or intention. However accepting the possibility of a simulation of the functional identity involving mind, but never structural identity.
accepted the creation of a sufficiently complex algorithm that could be encoded by a computer program and control a robot in the same way you would a human.


2. Systems:
this group are less concerned about philosophical issues, although its membership is in a weak AI. For them the goal is to build perfect machines, learning to represent and manipulate the knowledge about the real world through a computer and do not care in the least if the thinking of the machines is somehow related to the human way of thinking.

For these researchers the machine is the subject of his research, which is viewed as a whole (soft and hard) and it is intended that such scope and levels of intelligence, probably not made by man, increasingly advanced. And he speculates that the machine replaces the man, given the limitless possibilities of it.

The largest contributions to the field of AI should be in this group in key areas such as: robotics, technology knowledge, distributed AI, Lisp machines, etc.

3. Commercial systems:
applications are developed to solve problems that previously were the domain only of humans. Computer specialists are dedicated to addressing algorithms through unstructured tasks for practical purposes, often using complex data structures.

can be seen as a branch of engineering dedicated to creating commercial products. especially expert systems. For example, expert systems (which will be discussed in item 3).

Each approach creates a work philosophy that makes it incompatible communication between each group of researchers, from their "beliefs" of mind, machines and users. Even see how the machine changed for everyone.

Gone are the days when the IA was seen as a mystical science full of threats, some thought would replace expert systems specialist, today with a more mature without false expectations, remember the 5th Japanese project. Generation of AI techniques will gradually pass imperceptibly, it is more, it appears that intelligence will be expanded and that cooperation between humans and intelligent systems will emerge the bases of knowledge-based societies. Hence

IA abandon the autistic systems (enclosed in itself) to allow open systems to share information intelligently, in turn allowing the combination of different knowledge representation paradigms such as those based on rules, frames (frames ) scripts. And new research issues arise such as:
- The formalization of common sense.
- Learning.
- The integration of different paradigms of intelligence.
- The complete cognitive architecture development.

While Artificial Intelligence bleeds in infighting and define what is and is not Artificial Intelligence, in computing conventional hardware running at a rapid pace in the construction of ever faster machines with more memory and more likely to symbolic calculations, which is forecast to reach the creation of intelligent machines in the short term without Artificial Intelligence.

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Artificial Intelligence Cybernetics

Cybernetics In our day should not be seen either as a science, nor as a discipline, but as an ideological movement, which sought to break with the narrow expertise of each discipline. Cyber \u200b\u200bmovement allowed scientists of many different branches are grouped in groups of research and for the first time, mathematicians, physiologists and specialists in electronics to be integrated into multidisciplinary teams. Its founder Norbert Wiener after years working on mathematical theories and formulas to add some great mathematical apparatus, began working on technical issues such as control of anti-aircraft artillery fire and more efficient transmission of coded messages through communications systems. Wrote a book on cybernetics and control in animals and machines became a success. The stage was set for a new revolution in science.

Cybernetics is based on the study of machines (objects artificial) and their application, which promoted a new scientific revolution based on the interaction of humans with machines at a pace never before seen technological growth and unpredictability. This rate is already being felt and we can say, for example, that a man of the sixteenth century could very well have lived without many surprises in the seventeenth century instead one of the nineteenth century would have great trouble adapting to the twentieth and everything indicates that this acceleration will continue to increase, which will make a person in his old age has to live in a world completely different from your childhood.

With cybernetics machine concept has been changing over the years. After those first mechanical machines which sought to completely or partially replace physical labor of man and animals, have followed others, whose aim is the mechanization of mental labor. Today the machines perform functions that were previously considered characteristic of the human intellect. But perhaps the most important contribution of cybernetics was founded on analogies, hence exogenous characteristic of science, which is given by the interaction with other branches of knowledge and internal assimilation, but mainly by the proposed general theories explain phenomena of the other sciences. For example, cybernetics preferred based on model theory, which places more emphasis on the functional representation of bodies in their structure in the vertical or hierarchical. This, coupled with the search for analogies between the phenomena and not to the reduction of one another led her to become a scientific ideology for understanding the world. Another

contributions of cybernetics is the use of mathematical apparatus, which until then was used almost exclusively as physics and cybernetics in turn was a common discipline to several research areas, which resulted branches of psychology, sociology and biology, could somehow formalize their theories, and even went so far as methods of testing were provided through the creation of machinery for study behaviors, reactions, reflexes, learning, etc.
cyber
When trying to model the structure of an object rather than the structure they had in mind was the reproduction of his work on another structure and is aimed for the artificial object model or exhibit a behavior similar to the original. I say similar because in reality the behavior shown by the models has always been subject to the interpretation of the researcher. These attempts at modeling led researchers to build machines with behavior such as turtles and foxes Grey Walter Albert Ducrocq, which were nothing more than small machines with movement and is guided by the light, others are guided by sound or had some form of radar. But most interesting was the interpretation that was given to the behavior of these ciberanimalitos. For Grey Walter turtles could move from one to another irascible phlegmatic behavior. To Ducrocq, its foxes were able to express feelings of affection between them. I know this to rationalists may seem childish, but is not it interesting, if not true, that human beings continue using your imagination to interpret the phenomena and to keep alive in these times of scientific determinism, its ability to "surprise"?.

Today nobody talks about emotional experiences with turtles, foxes, mice ... The ideas were very simple: any device could show some form of human behavior. That was the dream of the cyber-Play life in all its forms and not just intelligence, as claimed in these times of Artificial Intelligence. And it did not base the Cybernetics his research on the basis that the machine would replace the man, who always saw both as systems with functional analogies, that while they large differences, because agencies own organizational structure and turn-possessed many similarities, hence the cyber gave him, ever greater emphasis on the influence of structure on the mind, but both viewed as a system capable of function as a whole.

live in a world of both social and spiritual crisis, and the desperate man turns his eyes to science and it expects the solution to major problems that overwhelm and cyber-ideology sees a new approach. Here are some of the problems are returning: The education system, health (the prosthesis), death, creativity, consumer goods production, development, understanding the human mind, happiness, evolution (convergence men and machines), new forms of social organization (posthumanity), human enhancement (man-machine connection)

is why Cybernetics passing of the years has been transformed into one of the ideologies of the most influential science, and like Physics and Biology, engenders great promise and for many it becomes the new savior of the world because it has provided one of the richest metaphors and powerful: the so-called computer metaphor or cybernetics, offering a new vision of society and opens the door to a new post-industrial era. Today there are many who think that the machine will replace the man, or those who believe that the human mind can be simulated by a computer, or who dream of creating artificial life.