Steve Kroon PLEASED: Planning, Learning, and Search for - - PowerPoint PPT Presentation

▶

Nov 01, 2022 577 likes •722 views

Steve Kroon PLEASED: Planning, Learning, and Search for Decision-making. http://www.cs.sun.ac.za/~kroon/decision.html Maties Machine Learning: 25 October 2019 This group considers almost any aspect of the general decision-making problem,

SLIDE 1

Steve Kroon

PLEASED: Planning, Learning, and Search for Decision-making. http://www.cs.sun.ac.za/~kroon/decision.html

Maties Machine Learning: 25 October 2019

SLIDE 2

“This group considers almost any aspect of the general decision-making problem, including sequential decision-making under uncertainty. Major sub-problems we consider are planning, machine learning, and search algorithms. Our approach is grounded in probability theory and game theory for managing uncertainty and multi-agent systems.”

Images: https://mimiandeunice.com/wp-content/uploads/2011/08/ME_447_Decisions-640x199.png

SLIDE 3

Single agent, single decision

Principled - grounded in:

Probability theory
Decision theory
Game theory

Typically requires:

A model (perhaps >1)
Data
Payoff function

Good foundation: Bayesian decision theory

Images:https://www.azimuthproject.org/azimuth/files/BayesianSDT-bigpic.png

SLIDE 4

Extensions

Sequential decision making

○ Search ○ Planning ○ Bayes filter ○ Reinforcement learning

Multi-agent settings

○ Adversarial ○ Collaborative

Tractable inference/decision making

○ Inference approaches ○ Search techniques ○ Choice of approximations

Images:https://www.azimuthproject.org/azimuth/files/BayesianSDT-bigpic.png

SLIDE 5

Group members

SLIDE 6

Learning theory*

*understanding relationships between and properties of machine learning/statistical models and approaches to fitting them

SLIDE 7

Search/Planning

SLIDE 8

Bayesian analysis

Images: https://miro.medium.com/max/1002/1*hblsrFOWViHS43l5YpUXeQ.png

SLIDE 9

Latent variable models/ variational inference

Images:https://miro.medium.com/max/800/1*pZo_IcxW1GVuH2vQKdoIMQ.jpeg

SLIDE 10

Process monitoring and fault detection/diagnosis

Images:https://www.ericsson.com/49d220/assets/global/qbank/2019/06/13/architecture-50-109173resize436234crop00436234autoorientquality90stripbackground23ffffffextensionjpgid8.jpg

SLIDE 11

Specific interests

Learning Theory* (mostly NNs) Search/Planning (mostly MCTS) Bayesian analysis Latent variable models and variational inference Process monitoring, fault detection and diagnosis