Скачать или смотреть Key Problem-Solving Strategies in AI

AI has revolutionized the way we approach problem-solving. From everyday applications like virtual assistants to complex systems in healthcare and finance, AI leverages many strategies to tackle diverse challenges. In this video, I highlight various problem-solving strategies in AI, not only neural network-based but also classical ones.

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https://machinelearning4all.com/key-p...

Topics Covered:

1. Search Algorithms in AI
Uninformed Search Algorithms:
Breadth-First Search (BFS)
Depth-First Search (DFS)
Uniform Cost Search

Informed Search Algorithms:
A* Search
Greedy Best First Search

2. Optimization Techniques
Gradient Descent
Genetic Algorithms
Simulated Annealing

3. Constraint Satisfaction Problems (CSPs)
Backtracking
Local Search Techniques (Hill Climbing, Simulated Annealing, Genetic Algorithms)

4. Logical Reasoning
Propositional Logic
First Order Logic

5. Probabilistic Methods
Bayesian Networks
Markov Decision Processes (MDPs)

6. Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning

7. Knowledge Representation and Reasoning
Semantic Networks
Frames

8. Natural Language Processing (NLP)
Parsing
Semantic Analysis

9. Game Theory
Minimax Algorithm
Alpha Beta Pruning

10. Expert Systems
Rule-Based Reasoning
Applications in Medical Diagnosis, Finance, Engineering

11. Case-Based Reasoning (CBR)
Solving new problems by leveraging solutions from past cases
Retrieval, Reuse, Revise, and Retain stages
The problem-solving strategies in AI are diverse and powerful, each with its unique strengths and applications. Understanding these strategies is crucial for anyone looking to harness the full potential of AI in their work or research.

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Dr. Shahriar Hossain
https://computing4all.com