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Artificial Intelligence. Bo Yuan, Ph.D. Professor Shanghai Jiaotong University. Overview of Machine Intelligence. Knowledge-based rules (expert system, automata, …) Symbolic representation in logics (Deep Blue) Kernel-based heuristics (MDA, PCA, SVM, …)
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Artificial Intelligence Bo Yuan, Ph.D. Professor Shanghai Jiaotong University
Overview of Machine Intelligence • Knowledge-based rules (expert system, automata, …) • Symbolic representation in logics (Deep Blue) • Kernel-based heuristics (MDA, PCA, SVM, …) • Nonlinear connection for more representation (Neural Network) • Inference (Bayesian, Markovian, …) • To sparsely sample for convergence (GM) • Interactive and stochastic computing (uncertainty, heterogeneity) • To possibly overcome the limit of Turin Machine
Top-Down Bottom-Up InteractionsThe Framework to Study a System
How much can we represent and model a complex and evolving network ?
Low Complexity Solutions forHigh Complexity Problems • Convexity • Stability (Metastability) • Sampling • Ergodicity • Convergence • Regularization • Software and Hardware
Top-Down Bottom-Up InteractionsThe Framework to Study a System
How much can we represent and model a complex and evolving network ?
Review of Lecture One • Overview of AI • Knowledge-based rules in logics (expert system, automata, …) : Symbolism in logics • Kernel-based heuristics (neural network, SVM, …) : Connection for nonlinearity • Learning and inference (Bayesian, Markovian, …) : To sparsely sample for convergence • Interactive and stochastic computing (Uncertainty, heterogeneity) : To overcome the limit of Turin Machine • Course Content • Focus mainly on learning and inference • Discuss current problems and research efforts • Perception and behavior (vision, robotic, NLP, bionics …) not included • Exam • Papers (Nature, Science, Nature Review, Modern Review of Physics, PNAS, TICS) • Course materials
Outline • Knowledge Representation • Searching and Logics • Perceiving and Acting • Learning • Uncertainty and Inference