Core Concepts of Artificial Intelligence and Problem-Solving with Python

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Part 3: Core Concepts of AI and Problem-Solving with Python

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What Is Intelligence in AI?

In AI, intelligence refers to the ability of a machine to:

  • Learn from experience
  • Adapt to new inputs
  • Perform tasks like reasoning, planning, and decision-making

Core Areas of AI

  1. Problem Solving

  2. Knowledge Representation

  3. Logical Reasoning

  4. Learning and Adaptation

Types of AI (By Capability)

Type Description Example
Narrow AI AI that performs a specific task Siri, Alexa
General AI AI that mimics human intelligence Still theoretical
Super AI AI smarter than humans Hypothetical/Future

Problem-Solving in AI

AI systems often solve problems using one or more of the following strategies:

1. Search Algorithms

Used to explore all possible solutions in a structured way (like in a maze or game).

Example: Breadth-First Search (BFS), Depth-First Search (DFS)

2. Heuristics

A heuristic is a rule of thumb or shortcut that guides decision-making.

# A simple heuristic: Prefer shorter paths
def heuristic(path):
    return len(path)

3. Rule-Based Systems

These systems use if-then rules to simulate decision-making.

def chatbot_response(message):
    if "hello" in message.lower():
        return "Hi there! How can I help you?"
    elif "bye" in message.lower():
        return "Goodbye!"
    else:
        return "I don't understand."

print(chatbot_response("Hello"))

Mini Project: A Simple Rule-Based Expert System

Let’s simulate a basic medical diagnosis bot using if-elif rules:

def diagnose(symptom):
    if symptom == "fever":
        return "You might have the flu."
    elif symptom == "cough":
        return "You may have a cold."
    elif symptom == "headache":
        return "Could be a migraine."
    else:
        return "Symptom not recognized."

print(diagnose("fever"))  # Output: You might have the flu.

Practice Challenge

Try expanding the system to handle multiple symptoms:

def multi_symptom(symptoms):
    if "fever" in symptoms and "cough" in symptoms:
        return "Flu or COVID-19"
    elif "headache" in symptoms and "nausea" in symptoms:
        return "Migraine"
    else:
        return "Please consult a doctor"

print(multi_symptom(["fever", "cough"]))

What You’ve Learned:

  • How AI systems approach problem-solving
  • The concept of heuristics and rules
  • How to implement rule-based systems using Python

What’s Next?

In Part 4, we’ll jump into Machine Learning and use Python’s scikit-learn to build your first ML model.


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