San Marcos National University
(Peruvian University dean of America)
FACULTY OF ENGINEERING AND COMPUTER SYSTEMS
Professional Academic School of Systems Engineering
(Peruvian University dean of America)
FACULTY OF ENGINEERING AND COMPUTER SYSTEMS
Professional Academic School of Systems Engineering
Week | Topics | Jobs |
1 ° | Week: Classification of algorithmic problems Presentation of the course. Classification of algorithmic problems, problems P and NP. Decision problems, localization and optimization. . Description of some NP-hard problems. References: [4] Chapter 1, [1] Annex A. | |
2 ° | Week: Fundamentals of Artificial Intelligence -Definition of Artificial Intelligence. Intelligent machines. -Applications in industry and services. (Robotics, planning, management waste) Review of artificial intelligence languages. Applications in industry and services. (Robotics, planning, waste management) - Turing Test References: [4] Chapter 1, [1] Annex A. | |
3 ° | Week: search methods in a state space - Definition of AI problems as search problems in a space of state. - Representation on Problem Gambling human - machine. References: [4] Chapter 1, [1] Annex A. | |
4 ° | Week: Blind Search Methods Blind search methods: amplitude,depth and not deterministic. References: [4] Chapter 1, [1] Annex A. | |
5 ° | Week: Informed Search Methods. Methods that use additional information: first the best, climb the hill, branching and bounding. References: [4] Chapter 1, [1] Annex A. | |
6 ° | Week: Search methods for man-machine games MIN-MAX methods to develop intelligent man-machine games. References: [4] Chapter 1, [1] Annex A. | |
7 ° | Week: Fundamentals of Expert Systems Fundamentals of Expert Systems: Definition of Expert Systems. Expert System Architecture | |
8 ° | Midterm Exam | |
9 ° | Week: Introduction of computational work Students show their skills in the development of game software-based intelligent search techniques. Se It shall submit a report and software, and must exhibit their work. | |
10 ° | Week: Knowledge Engineering Introduction. Acquisition of knowledge. The CommonKADS methodology. . Design of Expert Systems (ES). . Life cycle of an SE. References: [6] Chapters 6, [7] Chapter 19. | |
11 ° | Semana: Adquisición de Conocimiento Week: Knowledge Acquisition Adquisición de conocimiento. Acquisition of knowledge. Construcción de la base de hechos y base de conocimiento. Construction of the basis of facts and knowledge base. Estructuras de representación de conocimientos Knowledge representation structures (Rules of inference, frames, objects, semantic networks, predicate logic). References: [6] Chapters 6, [7] Chapter 19. 3rd reading control | |
12 ° | Week: Development of rule-based expert systems Construction of the basis of facts and knowledge base. The inference engine. Chaining methods, progressive and reversibility. Matching techniques, the RETE algorithm. Conflict resolution techniques. References: [1] Chapters 6 and 8, [2] Chapter 7 [6] Chapter 3, [7] Chapter 3. | |
13 ° | Week: Quality and validation of expert systems Major errors in the development of an expert system. Quality of an expert system. Validation of intelligent systems, methods quantitative validation. Error Efficiency and expert systems. Review of the functionality of SE 2nd job. Tasks: quality and validation exercises SE, validate the proposed system the 2nd job. References: [4], [7] Chapter 21. Read the 4th control | |
14° | Week: Introduction to Machine Learning (Machine Learning) and heuristics. Concepts of learning and machine learning. machine learning vs. expert systems. Learning techniques and stages of development machine learning. Machine learning applications in industry and services. Concepts of heuristics and meta-heuristics. Algoritmos Algorithms exact vs. heuristic algorithms. Técnicas heurísticas y meta-heurísticas. Heuristics and meta-heuristics. Optimization problems in industry and servicios services References: [5] Chapter 1 and 2, [8] Chapter 1, [10], [11]. | |
15° | Week: Introduction of computational work Students show their skills in the development of expert systems and their applications in the sectors of industry and service. The students will present a report and software. | |
16° | Week Final Exam |