AI-APPROACH
Artificial intelligence: A modern approach
- 30 Lecciones interactivas y 187 topics mapped to the official exam objectives
Intermediate A tu propio ritmo · 1 año de acceso 4.8/5 (229 Revisar)
30Lecciones interactivas
187Topics
146Tarjetas didácticas
146Glosario de términos
01 / Lecciones y laboratorios
See exactly what you will learn and practice
Plan de estudios
30 Lecciones interactivas · 187 topics01 Introduction 5 topics +
- What Is AI?
- The Foundations of Artificial Intelligence
- The History of Artificial Intelligence
- The State of the Art
- Summary, Bibliographical and Historical Notes, Exercises
02 Intelligent Agents 5 topics +
- Agents and Environments
- Good Behavior: The Concept of Rationality
- The Nature of Environments
- The Structure of Agents
- Summary, Bibliographical and Historical Notes, Exercises
03 Solving Problems by Searching 8 topics +
- Problem-Solving Agents
- Example Problems
- Searching for Solutions
- Uninformed Search Strategies
- Informed (Heuristic) Search Strategies
- Heuristic Functions
- Finding Relevant Code
- Summary, Bibliographical and Historical Notes, Exercises
04 Beyond Classical Search 6 topics +
- Local Search Algorithms and Optimization Problems
- Local Search in Continuous Spaces
- Searching with Nondeterministic Actions
- Searching with Partial Observations
- Online Search Agents and Unknown Environments
- Summary, Bibliographical and Historical Notes, Exercises
05 Adversarial Search 9 topics +
- Games
- Optimal Decisions in Games
- Alpha–Beta Pruning
- Imperfect Real-Time Decisions
- Stochastic Games
- Partially Observable Games
- State-of-the-Art Game Programs
- Alternative Approaches
- Summary, Bibliographical and Historical Notes, Exercises
06 Constraint Satisfaction Problems 6 topics +
- Defining Constraint Satisfaction Problems
- Constraint Propagation: Inference in CSPs
- Backtracking Search for CSPs
- Local Search for CSPs
- The Structure of Problems
- Summary, Bibliographical and Historical Notes, Exercises
07 Logical Agents 8 topics +
- Knowledge-Based Agents
- The Wumpus World
- Logic
- Propositional Logic: A Very Simple Logic
- Propositional Theorem Proving
- Effective Propositional Model Checking
- Agents Based on Propositional Logic
- Summary, Bibliographical and Historical Notes, Exercises
08 First-Order Logic 5 topics +
- Representation Revisited
- Syntax and Semantics of First-Order Logic
- Using First-Order Logic
- Knowledge Engineering in First-Order Logic
- Summary, Bibliographical and Historical Notes, Exercises
09 Inference in First-Order Logic 6 topics +
- Propositional vs. First-Order Inference
- Unification and Lifting
- Forward Chaining
- Backward Chaining
- Resolution
- Summary, Bibliographical and Historical Notes, Exercises
10 Classical Planning (Supplemental) 6 topics +
- Definition of Classical Planning
- Algorithms for Planning as State-Space Search
- Planning Graphs
- Other Classical Planning Approaches
- Analysis of Planning Approaches
- Summary, Bibliographical and Historical Notes, Exercises
11 Planning and Acting in the Real World 5 topics +
- Time, Schedules, and Resources
- Hierarchical Planning
- Planning and Acting in Nondeterministic Domains
- Multiagent Planning
- Summary, Bibliographical and Historical Notes, and Exercise
12 Knowledge Representation 8 topics +
- Ontological Engineering
- Categories and Objects
- Events
- Mental Events and Mental Objects
- Reasoning Systems for Categories
- Reasoning with Default Information
- The Internet Shopping World
- Summary, Bibliographical and Historical Notes, Exercises
13 Quantifying Uncertainty 7 topics +
- Acting under Uncertainty
- Basic Probability Notation
- Inference Using Full Joint Distributions
- Independence
- Bayes' Rule and Its Use
- The Wumpus World Revisited
- Summary, Bibliographical and Historical Notes, Exercises
14 Probabilistic Reasoning 8 topics +
- Representing Knowledge in an Uncertain Domain
- The Semantics of Bayesian Networks
- Efficient Representation of Conditional Distributions
- Exact Inference in Bayesian Networks
- Approximate Inference in Bayesian Networks
- Relational and First-Order Probability Models
- Other Approaches to Uncertain Reasoning
- Summary, Bibliographical and Historical Notes, Exercises
15 Probabilistic Reasoning over Time (Supplemental) 7 topics +
- Time and Uncertainty
- Inference in Temporal Models
- Hidden Markov Models
- Kalman Filters
- Dynamic Bayesian Networks
- Keeping Track of Many Objects
- Summary, Bibliographical and Historical Notes, Exercises
16 Making Simple Decisions (Supplemental) 8 topics +
- Combining Beliefs and Desires under Uncertainty
- The Basis of Utility Theory
- Utility Functions
- Multiattribute Utility Functions
- Decision Networks
- The Value of Information
- Decision-Theoretic Expert Systems
- Summary, Bibliographical and Historical Notes, Exercises
17 Making Complex Decisions (Supplemental) 7 topics +
- Sequential Decision Problems
- Value Iteration
- Policy Iteration
- Partially Observable MDPs
- Decisions with Multiple Agents: Game Theory
- Mechanism Design
- Summary, Bibliographical and Historical Notes, Exercises
18 Learning from Examples 12 topics +
- Forms of Learning
- Supervised Learning
- Learning Decision Trees
- Evaluating and Choosing the Best Hypothesis
- The Theory of Learning
- Regression and Classification with Linear Models
- Artificial Neural Networks
- Nonparametric Models
- Support Vector Machines
- Ensemble Learning
- Practical Machine Learning
- Summary, Bibliographical and Historical Notes, Exercises
19 Knowledge in Learning 8 topics +
- A Logical Formulation of Learning
- Knowledge in Learning
- Explanation-Based Learning
- Learning Using Relevance Information
- Inductive Logic Programming
- Feature Space Engineering
- Data Preparation and Preprocessing
- Summary, Bibliographical and Historical Notes, Exercises
20 Learning Probabilistic Models 4 topics +
- Statistical Learning
- Learning with Complete Data
- Learning with Hidden Variables: The EM Algorithm
- Summary, Bibliographical and Historical Notes, Exercises
21 Reinforcement Learning 7 topics +
- Introduction
- Passive Reinforcement Learning
- Active Reinforcement Learning
- Generalization in Reinforcement Learning
- Policy Search
- Applications of Reinforcement Learning
- Summary, Bibliographical and Historical Notes, Exercises
22 Natural Language Processing (Supplemental) 5 topics +
- Language Models
- Text Classification
- Information Retrieval
- Information Extraction
- Summary, Bibliographical and Historical Notes, Exercises
23 Natural Language for Communication (Supplemental) 6 topics +
- Phrase Structure Grammars
- Syntactic Analysis (Parsing)
- Augmented Grammars and Semantic Interpretation
- Machine Translation
- Speech Recognition
- Summary, Bibliographical and Historical Notes, Exercises
24 Perception (Supplemental) 7 topics +
- Image Formation
- Early Image-Processing Operations
- Object Recognition by Appearance
- Reconstructing the 3D World
- Object Recognition from Structural Information
- Using Vision
- Summary, Bibliographical and Historical Notes, Exercises
25 Robotics 9 topics +
- Introduction
- Robot Hardware
- Robotic Perception
- Planning to Move
- Planning Uncertain Movements
- Moving
- Robotic Software Architectures
- Application Domains
- Summary, Bibliographical and Historical Notes, Exercises
26 Focus: Robotics and Feature Engineering 2 topics +
- Coppelia Robotics
- Robotics: Feature Engineering
27 Philosophical Foundations 4 topics +
- Weak AI: Can Machines Act Intelligently?
- Strong AI: Can Machines Really Think?
- The Ethics and Risks of Developing Artificial Intelligence
- Summary, Bibliographical and Historical Notes, Exercises
28 AI: The Present and Future 4 topics +
- Agent Components
- Agent Architectures
- Are We Going in the Right Direction?
- What If AI Does Succeed?
29 Appendix A: Mathematical background 3 topics +
- A.1 Complexity Analysis and O() Notation
- A.2. Vectors, Matrices, and Linear Algebra
- A.3 Probability Distributions
30 Appendix B: Notes on Languages and Algorithms 2 topics +
- B.1 Defining Languages with Backus–Naur Form (BNF)
- B.2 Describing Algorithms with Pseudocode
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