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Artificial Intelligence in Wireless Robotics
Robots, autonomous vehicles, unmanned aerial vehicles, and smart factories will significantly change human living style in digital society. Artificial Intelligence in Wireless Roboticsintroduces how wireless communications and networking technology enhances facilitation of artificial intelligence in...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Aalborg :
River Publishers,
2020.
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| Colección: | River Publishers Series in Information Science and Technology Ser.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Chen, Kwang-Cheng. | |
| 245 | 1 | 0 | |a Artificial Intelligence in Wireless Robotics |
| 260 | |a Aalborg : |b River Publishers, |c 2020. | ||
| 300 | |a 1 online resource (356 pages) | ||
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| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Front Cover -- Artificial Intelligence in Wireless Robotics -- Contents -- Preface -- List of Figures -- List of Tables -- List of Abbreviations -- 01 Introduction to Artificial Intelligence and Robotics -- 1.1 Common Sense Knowledge of AI, Cybernetics, and Robotics -- 1.2 Intelligent Agents -- 1.2.1 The Concept of Rationality -- 1.2.2 System Dynamics -- 1.2.3 Task Environments -- 1.2.4 Robotics and Multi-Agent Systems -- 1.3 Reasoning -- 1.3.1 Constraint Satisfaction Problems -- 1.3.2 Solving CSP by Search -- References -- 02 Basic Search Algorithms -- 2.1 Problem-Solving Agents | |
| 505 | 8 | |a 2.2 Searching for Solutions -- 2.3 Uniform Search -- 2.3.1 Breadth-First Search -- 2.3.2 Dynamic Programming -- 2.3.3 Depth-first Search -- 2.4 Informed Search -- 2.5 Optimization -- 2.5.1 Linear Programming -- 2.5.2 Nonlinear Programming -- 2.5.3 Convex Optimization -- References -- 03 Machine Learning Basics -- 3.1 Supervised Learning -- 3.1.1 Regression -- 3.1.2 Bayesian Classification -- 3.1.3 KNN -- 3.1.4 Support Vector Machine -- 3.2 Unsupervised Learning -- 3.2.1 K-Means Clustering -- 3.2.2 EM Algorithms -- 3.2.3 Principal Component Analysis -- 3.3 Deep Neural Networks | |
| 505 | 8 | |a 4.5.3 Thompson Sampling -- References -- 05 Reinforcement Learning -- 5.1 Fundamentals of Reinforcement Learning -- 5.1.1 Revisit of Multi-Armed Bandit Problem -- 5.1.2 Basics in Reinforcement Learning -- 5.1.3 Reinforcement Learning Based on Markov Decision Process -- 5.1.4 Bellman Optimality Principle -- 5.2 Q-Learning -- 5.2.1 Partially Observable States -- 5.2.2 Q-Learning Algorithm -- 5.2.3 Illustration of Q-Learning -- 5.3 Model-Free Learning -- 5.3.1 Monte Carlo Methods -- 5.3.2 Temporal Difference Learning -- 5.3.3 SARSA -- 5.3.4 Relationship Between Q-Learning and TD-Learning | |
| 504 | |a References-06 State Estimation-6.1 Fundamentals of Estimation-6.1.1 Linear Estimator from Observations-6.1.2 Linear Prediction-6.1.3 Bayesian Estimation-6.1.4 Maximum Likelihood Estimation-6.2 Recursive State Estimation-6.3 Bayes Filters-6.4 Gaussian Filters-6.4.1 Kalman Filter-6.4.2 Scalar Kalman Filter-6.4.3 Extended Kalman Filter-References-07 Localization-7.1 Localization By Sensor Network-7.1.1 Time-of-Arrival Techniques-7.1.2 Angle-of-Arrival Techniques-7.1.3 Time-Difference-of-Arrivals Techniques-7.2 Mobile Robot Localization. | ||
| 500 | |a 7.3 Simultaneous Localization and Mapping. | ||
| 520 | |a Robots, autonomous vehicles, unmanned aerial vehicles, and smart factories will significantly change human living style in digital society. Artificial Intelligence in Wireless Roboticsintroduces how wireless communications and networking technology enhances facilitation of artificial intelligence in robotics, which bridges basic multi-disciplinary knowledge among artificial intelligence, wireless communications, computing, and control in robotics. A unique aspect of the book is to introduce applying communication and signal processing techniques to enhance traditional artificial intelligence i. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Autonomous robots. | |
| 650 | 0 | |a Wireless communication systems. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 2 | |a Artificial Intelligence | |
| 650 | 2 | |a Wireless Technology | |
| 650 | 6 | |a Robots autonomes. | |
| 650 | 6 | |a Transmission sans fil. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Artificial intelligence |2 fast | |
| 650 | 7 | |a Autonomous robots |2 fast | |
| 650 | 7 | |a Wireless communication systems |2 fast | |
| 758 | |i has work: |a Artificial Intelligence in Wireless Robotics (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFY7pr3FRHfqHgcm46GW6q |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Chen, Kwang-Cheng. |t Artificial Intelligence in Wireless Robotics. |d Aalborg : River Publishers, ©2020 |z 9788770221184 |
| 830 | 0 | |a River Publishers Series in Information Science and Technology Ser. | |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=6406229 |z Texto completo |
| 880 | 8 | |6 505-00/(S |a 3.4 Data Preprocessing -- References -- 04 Markov Decision Processes -- 4.1 Statistical Decisions -- 4.1.1 Mathematical Foundation -- 4.1.2 Bayes Decision -- 4.1.3 Radar Signal Detection -- 4.1.4 Bayesian Sequential Decision -- 4.2 Markov Decision Processes -- 4.2.1 Mathematical Formulation of Markov Decision Process -- 4.2.2 Optimal Policies -- 4.2.3 Developing Solutions to Bellman Equation -- 4.3 Decision Making and Planning: Dynamic Programming -- 4.4 Application of MDP to Search A Mobile Target -- 4.5 Multi-Armed Bandit Problem -- 4.5.1 ε-Greedy Algorithm -- 4.5.2 Upper Confidence Bounds | |
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