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Artificial Intelligence - Exploring the Future of Machine Learning and Robotics - cover

Artificial Intelligence - Exploring the Future of Machine Learning and Robotics

Fouad Sabry

Maison d'édition: One Billion Knowledgeable

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Synopsis

1: Artificial intelligence: This chapter introduces AI, outlining its evolution and core principles as the cornerstone of robotics.
 
2: Machine learning: Explores how machines learn from data and improve over time, a crucial component of AIdriven robotics.
 
3: Symbolic artificial intelligence: Covers symbolic AI's focus on rules and logic, essential for developing reasoning capabilities in robots.
 
4: Neats and scruffies: Delves into two approaches to AI, comparing structured versus heuristic methods in robotic development.
 
5: Peter Norvig: Examines Norvig's contributions to AI, focusing on his work in search algorithms and decisionmaking processes.
 
6: Artificial Intelligence: A Modern Approach: This chapter dives into the textbook by Stuart Russell and Peter Norvig, a key reference for AI practitioners.
 
7: Stuart J. Russell: Analyzes Russell's influential theories on AI, particularly his work on rational agents in robotics.
 
8: Artificial general intelligence: Discusses the concept of AGI and its potential to create robots with humanlike cognitive abilities.
 
9: AI takeover: Investigates the concerns surrounding AI surpassing human intelligence and its implications for robotics.
 
10: Computational intelligence: Explores the intersection of computation and intelligence, with emphasis on neural networks in robotics.
 
11: Synthetic intelligence: Looks at the creation of AI through artificial means, advancing the capabilities of robots.
 
12: Intelligent agent: Defines intelligent agents and how they are designed to operate autonomously in dynamic environments.
 
13: History of artificial intelligence: Traces the history of AI, providing a context for its current applications in robotics and beyond.
 
14: Philosophy of artificial intelligence: Discusses the ethical considerations and philosophical debates surrounding AI's role in society.
 
15: AI winter: Examines the periods of AI stagnation, offering lessons on overcoming obstacles in AI and robotics development.
 
16: Timeline of artificial intelligence: Provides a chronological account of key AI milestones, offering insights into its growth in robotics.
 
17: GOFAI: Introduces Good OldFashioned AI, explaining its foundational influence on modern robotic intelligence systems.
 
18: AI alignment: Discusses the alignment problem, focusing on how AI systems can be designed to align with human values.
 
19: Supervised learning: Focuses on supervised learning techniques and their application in training robots for specific tasks.
 
20: Neural network (machine learning): Covers neural networks and their importance in machine learning, with practical applications in robotics.
 
21: Pattern recognition: Explores pattern recognition techniques used by robots to process sensory data and make decisions.
Disponible depuis: 18/12/2024.
Longueur d'impression: 304 pages.

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