Feng Gang.Qin Shuang National Laboratory of Communication,UESTC Machine Intelligence Definition: Study of intelligent agents:any device that perceives its environment and takes actions that maximize its chance of success at some goal 。 Machine Learning belongs to one of the most important subfields in AI. Classification of ML algorithms Supervised Learning Supervised Unsupervised Unsupervised Learning Learning Learning Machine Reinforcement Learning Learning Reinforcement Learning Fig.classification of machine learning Advanced Topics in Computer Networks 11:AI Enabled Wireless Access Control and Handoff Page.6
Advanced Topics in Computer Networks Feng Gang, Qin Shuang National Laboratory of Communication, UESTC 11: AI Enabled Wireless Access Control and Handoff Page.6 Machine Intelligence • Definition: • Study of intelligent agents: any device that perceives its environment and takes actions that maximize its chance of success at some goal • Machine Learning belongs to one of the most important subfields in AI. • Classification of ML algorithms - Supervised Learning - Unsupervised Learning - Reinforcement Learning Fig. classification of machine learning
Feng Gang.Qin Shuang National Laboratory of Communication,UESTC Supervised Learning A supervised learning agent will be fed with "labeled"inputs and their desired outputs,and aims to determine a general rule that nicely maps inputs to outputs. e.g.,SVM algorithm,Wireless Channel Estimation 0 0 0 8 0 0 89 : 0 Advanced Topics in Computer Networks 11:AI Enabled Wireless Access Control and Handoff Page.7
Advanced Topics in Computer Networks Feng Gang, Qin Shuang National Laboratory of Communication, UESTC Supervised Learning • A supervised learning agent will be fed with “labeled” inputs and their desired outputs, and aims to determine a general rule that nicely maps inputs to outputs. • e.g., SVM algorithm, Wireless Channel Estimation 11: AI Enabled Wireless Access Control and Handoff Page.7
Feng Gang.Qin Shuang National Laboratory of Communication,UESTC Unsupervised Learning Unsupervised learning is the machine learning task of inferring a function to describe hidden structure from "unlabeled"inputs. e.g.,Clustering algorithm Cluster 0 Cluster 2 x-axs Advanced Topics in Computer Networks 11:AI Enabled Wireless Access Control and Handoff Page.8
Advanced Topics in Computer Networks Feng Gang, Qin Shuang National Laboratory of Communication, UESTC Unsupervised Learning • Unsupervised learning is the machine learning task of inferring a function to describe hidden structure from "unlabeled" inputs. • e.g., Clustering algorithm 11: AI Enabled Wireless Access Control and Handoff Page.8
Feng Gang.Qin Shuang National Laboratory of Communication,UESTC Reinforcement learning Inspired by control theory and behaviorist psychology,concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward in a Markov Decision Process(MDP). e.g.,Reinforcement learning algorithm Agent Action at Environment ⊙⊙ Reward rt State St+1 Reinforcement Learning Setup Advanced Topics in Computer Networks 11:AI Enabled Wireless Access Control and Handoff Page.9
Advanced Topics in Computer Networks Feng Gang, Qin Shuang National Laboratory of Communication, UESTC Reinforcement learning • Inspired by control theory and behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward in a Markov Decision Process (MDP). • e.g., Reinforcement learning algorithm 11: AI Enabled Wireless Access Control and Handoff Page.9
Feng Gang.Qin Shuang National Laboratory of Communication,UESTC Why AI in Wireless Networks Application Scenarios and Requirements:5G mobile networks Three use case families Extreme Mobile Broad Band (eMBB):extreme high throughputs and low-latency. - Massive Machine-Type Communications(mMTC):provides 100,000 wireless connections per AP. Ultra-reliable Low-Latency Communications (uRLLC):provides ultra- reliable low-latency and/or resilient communication links for network services. Advanced Topics in Computer Networks 11:AI Enabled Wireless Access Control and Handoff Page.10
Advanced Topics in Computer Networks Feng Gang, Qin Shuang National Laboratory of Communication, UESTC Why AI in Wireless Networks • Three use case families - Extreme Mobile Broad Band (eMBB)：extreme high throughputs and low-latency. - Massive Machine-Type Communications (mMTC): provides 100,000 wireless connections per AP. - Ultra-reliable Low-Latency Communications (uRLLC): provides ultrareliable low-latency and/or resilient communication links for network services. 11: AI Enabled Wireless Access Control and Handoff Page.10 Application Scenarios and Requirements: 5G mobile networks