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SOLUTIONS & INSTRUCTOR MANUAL for Artificial Intelligence: A Modern Approach, 4th Edition by Peter Norvig and Stuart Russell Updated A+

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SOLUTIONS & INSTRUCTOR MANUAL for Artificial Intelligence: A Modern Approach, 4th Edition by Peter Norvig and Stuart Russell Updated A+ 1 Introduction ... 1 2 Intelligent Agents ... 36 II Problem-solving 3 Solving Problems by Searching ... 63 4 Search in Complex Environments ... 110 5 Adversarial Search and Games ... 146 6 Constraint Satisfaction Problems ... 180 III Knowledge, reasoning, and planning 7 Logical Agents ... 208 8 First-Order Logic ... 251 9 Inference in First-Order Logic ... 280 10 Knowledge Representation ... 314 11 Automated Planning ... 344 IV Uncertain knowledge and reasoning 12 Quantifying Uncertainty ... 385 13 Probabilistic Reasoning ... 412 14 Probabilistic Reasoning over Time ... 461 15 Probabilistic Programming ... 500 16 Making Simple Decisions ... 528 17 Making Complex Decisions ... 562 18 Multiagent Decision Making ... 599 V Machine Learning 19 Learning from Examples ... 651 20 Learning Probabilistic Models ... 721 21 Deep Learning ... 750 22 Reinforcement Learning ... 789 VI Communicating, perceiving, and acting 23 Natural Language Processing ... 823 24 Deep Learning for Natural Language Processing ... 856 25 Computer Vision ... 881 26 Robotics ... 925 VII Conclusions 27 Philosophy, Ethics, and Safety of AI ... 981 28 The Future of AI ... 1012 Appendix A: Mathematical Background ... 1023 Appendix B: Notes on Languages and Algorithms ... 1030

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Artificial Intelligence: A Modern Approach
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SOLUTIONS & INSTRUCTOR MANUAL

Artificial Intelligence: A Modern Approach, 4th Edition

by Peter Norvig and Stuart Russell, Chapters 1 – 28

,Artificial Intelligence FC




FCFCFCFC 1 Introduction ...
FC FC FC




FCFCFCFC 2 Intelligent Agents ...
FC FC FC FC




II Problem-solving
FC




FCFCFCFC 3 Solving Problems by Searching ...
FC FC FC FC FC FC




FCFCFCFC 4 Search in Complex Environments ...
FC FC FC FC FC FC




FCFCFCFC 5 Adversarial Search and Games ...
FC FC FC FC FC FC




FCFCFCFC 6 Constraint Satisfaction Problems ...
FC FC FC FC FC




III Knowledge, reasoning, and planning
FC FC FC FC




FCFCFCFC 7 Logical Agents ...
FC FC FC FC




FCFCFCFC 8 First-Order Logic ...
FC FC FC FC




FCFCFCFC 9 Inference in First-Order Logic ...
FC FC FC FC FC




FCFCFCFC 10 Knowledge Representation ...
FC FC FC FC




FCFCFCFC 11 Automated Planning ...
FC FC FC FC




IV Uncertain knowledge and reasoning
FC FC FC FC




FCFCFCFC 12 Quantifying Uncertainty ...
FC FC FC FC

, 13 Probabilistic Reasoning ...
FCFCFCFC FC FC FC FC




14 Probabilistic Reasoning over Time ...
FCFCFCFC FC FC FC FC FC FC




15 Probabilistic Programming ...
FCFCFCFC FC FC FC FC




16 Making Simple Decisions ...
FCFCFCFC FC FC FC FC FC




17 Making Complex Decisions ...
FCFCFCFC FC FC FC FC FC




18 Multiagent Decision Making ...
FCFCFCFC FC FC FC FC FC




V Machine Learning
FC FC




19 Learning from Examples ...
FCFCFCFC FC FC FC FC FC




20 Learning Probabilistic Models ...
FCFCFCFC FC FC FC FC FC




21 Deep Learning ...
FCFCFCFC FC FC FC FC




22 Reinforcement Learning ...
FCFCFCFC FC FC FC FC




VI Communicating, perceiving, and acting
FC FC FC FC




23 Natural Language Processing ...
FCFCFCFC FC FC FC FC FC




24 Deep Learning for Natural Language Processing ...
FCFCFCFC FC FC FC FC FC FC FC FC




25 Computer Vision ...
FCFCFCFC FC FC FC FC




26 Robotics ...
FCFCFCFC FC FC FC




VII Conclusions FC

,FCFCFCFC 27 Philosophy, Ethics, and Safety of AI ...
FC FC FC FC FC FC FC FC




FCFCFCFC 28 The Future of AI
FC FC FC FC

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