Artificial Intelligence Search and Knowledge Systems
Heuristic Search and Hill Climbing Algorithms
A Heuristic Search is a search technique that uses heuristic information (rules or estimates) to find a solution faster than uninformed search methods.
A heuristic function is written as: h(n) = Estimated cost from node n to the goal.
Hill Climbing is a heuristic search algorithm that continuously moves toward the neighboring state with the highest value (better solution) until no better neighbor exists.
It is called “hill climbing” because it always tries
Read MorePatrones de Diseño y Buenas Prácticas en C# .NET
Patrones de Diseño Creacionales
Singleton
Propósito: Evitar instancias duplicadas.
public class S
{
private static S _i;
private S() { }
public static S Instance
{
get
{
if (_i == null) _i = new S();
return _i;
}
}
}Factory Method
Propósito: Uso de if/else para crear objetos.
public abstract class C
{
public P Crear(string t)
{
var p = CrearP(t);
p.Init();
return p;
}
protected abstract P CrearP(Artificial Intelligence Principles and Logic Systems
Search and Problem Solving in AI
1. Define AI
Artificial Intelligence (AI) is the branch of computer science that develops machines capable of performing tasks that normally require human intelligence.
2. What is an Intelligent Agent?
An Intelligent Agent is an entity that perceives its environment through sensors and acts upon it using actuators to achieve goals.
3. Define a Problem-Solving Agent.
A Problem-Solving Agent is an intelligent agent that finds a sequence of actions to reach a goal from an
Read MoreN-Gram Models and Statistical Language Modeling
N-Gram Models: Unigram, Bigram, and Trigram
An N-Gram Model is a statistical language model that predicts the next word based on the previous 
words.
Types of N-Grams
Unigram (N=1)
Considers each word independently.
Example sentence: I love NLP
Unigrams:
- I
- love
- NLP
Probability: 
Bigram (N=2)
Considers one previous word.
Bigrams:
- I love
- love NLP
Probability: 
Trigram (N=3)
Considers two previous words.
Trigrams:
- I love NLP
Probability: 
Applications of N-Grams
- Text prediction
- Spell checking
- Speech recognition
- Machine translation
- Chatbots
Statistical
Read MoreEssential Java Programming Examples and Core Concepts
Usage of Static and Global Variables
class VariableDemo {
private int instanceVar = 10;
private static int staticVar = 20;
public void displayVariables() {
int localVar = 30;
System.out.println("Instance Variable: " + instanceVar);
System.out.println("Static Variable: " + staticVar);
System.out.println("Local Variable: " + localVar);
}
public static void main(String[] args) {
VariableDemo demo = new VariableDemo();
demo.displayVariables(Essential Natural Language Processing Concepts and Tools
Generative Language Models
Definition: A Generative Language Model learns the probability distribution of words in a language and generates new text by predicting the next word or sequence of words based on context.
Example: For the input “The sun rises in the,” the model may predict “east,” resulting in “The sun rises in the east.”
Advantages
- Produces coherent text
- Useful for content generation
- Learns from large text corpora
- Supports various NLP applications