Presented by: ENNAHIBI Med KASMI Ilyas OUBAALLA Wafaa Supervised by: Mr ABELLAOUI Mohammed

Plan: Introduction. Intelligence in general. What is Artificial Intelligence? Historic of Artificial Intellignce: Turing test. Experts systems. What is an Expert system. Requirement of Expert System. Uses of experts systems. Architecture of experts systems. Automatic Learning and Neuro-fuzzy. Intelligent system. Appliances of Artificial Intelligence. Conclusion.

Introduction

Intelligence in general. Adaptability to a new environment or to changes in the current environment Capacity for knowledge and the ability to acquire it Capacity for reason and abstract thought Ability to comprehend relationships Ability to evaluate and judge Capacity for original and productive thought

What is Artificial Intelligence? Artificial intelligence allows computers to learn from experience, recognize patterns in large amounts of complex data and make complex decisions based on human knowledge and reasoning skills.

Turing Test The Turing test is a proposal for a test of a machine's ability to demonstrate intelligence.

What is an Expert System ? An expert system is software that attempts to reproduce the performance of one or more human experts, most commonly in a specific problem domain, and is a traditional application and/or subfield of artificial intelligence.

Requirement of Expert System: The creation of a so-called "knowledgebase" which uses some knowledge representation formalism to capture the Subject Matter Experts (SME) knowledge. A process of gathering that knowledge from the SME and codifying it according to the formalism, which is called knowledge engineering.

Uses of Expert System: As a first application of computing and artificial intelligence, the topic of expert systems has many points of contact with general systems theory, operations research, business process reengineering and various topics in applied mathematics and management science.

Architecture of Expert Systems: The sequence of steps taken to reach a conclusion is dynamically synthesized with each new case. It is not explicitly programmed when the system is built. Expert systems can process multiple values for any problem parameter. This permits more than one line of reasoning to be pursued and the results of incomplete (not fully determined) reasoning to be presented. Problem solving is accomplished by applying specific knowledge rather than specific technique.

Automatic Learning and Neuro-Fuzzy: In the field of artificial intelligence, neuro-fuzzy refers to combinations of artificial neural networks and fuzzy logic. Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks.

Requirement of Expert System : The creation of a so-called "knowledgebase" which uses some knowledge representation formalism to capture the Subject Matter Experts (SME) knowledge. A process of gathering that knowledge from the SME and codifying it according to the formalism, which is called knowledge engineering.

Uses of Expert System: As a first application of computing and artificial intelligence, the topic of expert systems has many points of contact with general systems theory, operations research, business process reengineering and various topics in applied mathematics and management science.

Architecture of Expert Systems : The sequence of steps taken to reach a conclusion is dynamically synthesized with each new case. It is not explicitly programmed when the system is built. Expert systems can process multiple values for any problem parameter. This permits more than one line of reasoning to be pursued and the results of incomplete (not fully determined) reasoning to be presented. Problem solving is accomplished by applying specific knowledge rather than specific technique.

Automatic Learning and Neuro-Fuzzy: In the field of artificial intelligence, neuro-fuzzy refers to combinations of artificial neural networks and fuzzy logic. Neuro-fuzzy hybridization results in a hybrid intelligent system that synergizes these two techniques by combining the human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks.

Intelligent Systems : “ In order to make great games, great tools and a great work environment are essential.” INTELLIGENT SYSTEMS began by supporting Nintendo game development from the very beginning. At first, development tools were required in order to develop game software.

Intelligent Systems II: “ INTELLIGENT SYSTEMS creates it own unique game development environment.” INTELLIGENT SYSTEMS grew not only as a game developer, but as a game environment and development tool developer as well.

Appliances of AI : Finance Banks use artificial intelligence systems to organize operations, invest in stocks, and manage properties. In August 2001, robots beat humans in a simulated financial trading competition. Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation.

Appliances of AI: Medicine A medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and provide medical information. They may also be used for medical diagnosis, Artificial neural networks are used for medical diagnosis (such as in Concept Processing technology in EMR software), functioning as machine differential diagnosis.

Appliances of AI: Heavy industry Robots have become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. General Motors uses around 16,000 robots for tasks such as painting, welding, and assembly. Japan is the leader in using and producing robots in the world. In 1995, 700,000 robots were in use worldwide; over 500,000 of which were from Japan.

Appliances of AI: Transportation Fuzzy logic controllers have been developed for automatic gearboxes in automobiles (the 2006 Audi TT, VW Toureg and VW Caravell feature the DSP transmission which utilizes Fuzzy logic, a number of Škoda variants (Škoda Fabia) also currently include a Fuzzy Logic based controller).

Appliances of AI: Toys and games The 1990s saw some of the first attempts to mass- produce domestically aimed types of basic Artificial Intelligence for education, or leisure. This prospered greatly with the Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of AI, specifically in the form of Tamagotchis and Giga Pets, the Internet (example: basic search engine interfaces are one simple form), and the first widely released robot, Furby. A mere year later an improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy. AI has also been applied to video games.

Appliances of AI: Music The evolution of music has always been affected by technology. With AI, scientists are trying to make the computer emulate the activities of the skillful musician. Composition, performance, music theory, sound processing are some of the major areas on which research in Music and Artificial Intelligence are focusing on.

Conclusion Artificial Intelligence is a field that requires immagination, it has a succeful future in industry, office also domestic use. Thus, video games, robotic, cybertic and nanotechnologie all of this exceptionnal phenomena are based on Artificial Intelligence... So be carefull because it is critical field, may be one day, it will turn on humain life.