A Knowledge-Based System uses a knowledge base to reason and solve complex problems. Thus, we could say that today any problem/system is a Knowledge Based System (KBS). The fundamental features that characterize a KBS are, as its name suggests, Knowledge, the Knowledge Representation, Reasoning and the Search that can be carried out on it. And these will be the axes that the subject will deal with.
Titular Professors
Professors
Advanced Programming and Data Structure
The goals of the course are:
- Know the scope of Artificial Intelligence and, in particular, the field of Knowledge-Based Systems.
- Be aware of the computational costs and the quality of the solutions of the different search algorithms.
- Be aware of the importance of knowledge, as well as how to deal with it.
- Develop a specific case: a Chatbot.
1. INTRODUCTION
1.1 Artificial Intelligence
1.2 Knowledge-Based Systems
2. KNOWLEDGE REPRESENTATION. REASONING
2.1 Knowledge representation. Concepts
2.2 Structured knowledge representation
2.3 Rule-based knowledge representation
3. DESCRIPTIVE ANALYTICS
3.1. Descriptive statistics
3.2. Clustering
4. PREDICTIVE ANALYTICS
4.1. Statistical reasoning
4.2. Machine Learning-based classification
5. PROBLEM SOLVING. SEARCH
5.1 Problem Solving. Concepts
5.2 Blind search
5.3 Heuristic search
5.4 Search for Constraint Satisfaction Problems
5.5 Adversary search
6. PROJECT: CHATBOT
6.1 What is a Chatbot?
6.2 Determine the domain/problem of your project. First implementation
6.3 Implementation of the project
6.4 Oral presentation
6.5 Written presentation in article format
Project class: NLP
Project class: Seminar
Project class: How to write a paper?
The methodology used combines master classes, the resolution of exercises, student participation, and the development of a project. For the student, this will involve both individual and groups works, as well as conceptual exercises, implemented exercises, oral presentations and written presentations. The course will follow two lines in parallel: 1) the master classes and the most conceptual exercises to advance the syllabus; and 2) the development of the project from the first day to the last class which will involve up to five deliveries: from the conceptualization of a Chatbot to its development with a final presentation.
This course uses a continuous assessment system, calculated as follows:
Final Grade = 40% Exercises Grade + 60% Project Grade
* provided that all exercises and all project components receive a minimum grade of 5 or higher.
Exercises Grade = 20% Assessment 1 + 20% Assessment 2 + 20% Assessment 3 + 20% Assessment 4 + 20% Assessment 5
Project Grade = [ 10% Project 1 (What Is a Chatbot?) + 20% Project 2 (First Implementation) + 5% Project 3 (Final Implementation) + 20% Project 4 (Oral Presentation) + 25% Project 5 (Article) + 15% Best Chatbot (voted by instructors) ] × (Peer-to-Peer points awarded / 100
* Understanding of KBS concepts and techniques
* Knowledge representation and modeling quality
* Design and implementation of the system
* Application of inference and reasoning methods
* Evaluation, validation, and critical analysis
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•Class/Lecture notes