Introduction to Artificial Intelligence with Python Knowledge knowledge-based agents agents that reason by operating on internal representations of knowledge If it didn’t rain, Harry visited Hagrid today. Harry visited Hagrid or Dumbledore today, but not both. Harry visited Dumbledore today. Harry did not visit Hagrid today. It rained today. Logic sentence an assertion about the […]
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Introduction to Artificial Intelligence with Python Artificial Intelligence X Search O X OX Knowledge P→Q P Q Uncertainty Optimization Inbox Learning Spam Neural Networks NP PP ADJ N P N artificial with intelligence python NP Language Search 1234 5678 9 101112 13 14 15 Search Problems agent entity that perceives its environment and acts upon
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Introduction to Artificial Intelligence with Python Optimization optimization choosing the best option from a set of options local search search algorithms that maintain a single node and searches by moving to a neighboring node B A B Cost: 17 state-space landscape objective function global maximum cost function global minimum current state neighbors Hill Climbing Hill
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CSCI E-80 Introduction to Artificial Intelligence with Python Harvard Extension School Fall 2020 0. Search 1. Knowledge 2. Uncertainty 3. Optimization 4. Learning 5. Neural Networks 6. Language Announcements Lectures Office Hours Projects Sections Staff Syllabus Ed Discussion Quick Start Guide Questions Write an AI to answer questions. $ python questions.py corpus Query: What are the
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CSCI E-80 Introduction to Artificial Intelligence with Python Harvard Extension School Fall 2020 0. Search 1. Knowledge 2. Uncertainty 3. Optimization 4. Learning 5. Neural Networks 6. Language Announcements Lectures Office Hours Projects Sections Staff Syllabus Ed Discussion Quick Start Guide Lecture 0 Artificial Intelligence Artificial Intelligence (AI) covers a range of techniques that appear as
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Introduction to Artificial Intelligence with Python Optimization optimization choosing the best option from a set of options local search search algorithms that maintain a single node and searches by moving to a neighboring node B A B Cost: 17 state-space landscape objective function global maximum cost function global minimum current state neighbors Hill Climbing Hill
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CSCI E-80 Introduction to Artificial Intelligence with Python Harvard Extension School Fall 2020 0. Search 1. Knowledge 2. Uncertainty 3. Optimization 4. Learning 5. Neural Networks 6. Language Announcements Lectures Office Hours Projects Sections Staff Syllabus Ed Discussion Quick Start Guide Lecture 1 Knowledge Humans reason based on existing knowledge and draw conclusions. The concept of
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CSCI E-80 Introduction to Artificial Intelligence with Python Harvard Extension School Fall 2020 0. Search 1. Knowledge 2. Uncertainty 3. Optimization 4. Learning 5. Neural Networks 6. Language Announcements Lectures Office Hours Projects Sections Staff Syllabus Ed Discussion Quick Start Guide Nim Write an AI that teaches itself to play Nim through reinforcement learning. $ python
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CSCI E-80 Introduction to Artificial Intelligence with Python Harvard Extension School Fall 2020 0. Search 1. Knowledge 2. Uncertainty 3. Optimization 4. Learning 5. Neural Networks 6. Language Announcements Lectures Office Hours Projects Sections Staff Syllabus Ed Discussion Quick Start Guide Knights Write a program to solve logic puzzles. Background In 1978, logician Raymond Smullyan published
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CSCI E-80 Introduction to Artificial Intelligence with Python Harvard Extension School Fall 2020 0. Search 1. Knowledge 2. Uncertainty 3. Optimization 4. Learning 5. Neural Networks 6. Language Announcements Lectures Office Hours Projects Sections Staff Syllabus Ed Discussion Quick Start Guide PageRank Write an AI to rank web pages by importance. $ python pagerank.py corpus0 PageRank
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