# 程序代写 Review on Reasoning about Uncertainty – cscodehelp代写

Artificial Intelligence
COSC1127/1125
Semester 2, 2021
Prof.

Some news…

Preliminary contest ranking here.
Base marks using Python script provided in #271
Marks may be adjusted by contributions.
Bonus Project 3 to be marked this week
Final Pacman Contest:
Agent system due Week 12
Instructions on Wiki and video coming soon
CES Survey closes soon?
Are you a better CS after this course?
Have you learnt new things as a CS?
THE Review: 2nd lectorial today!

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Congratulations
Mint to be 3!

Remaining assessments…

Instructions and Wiki template to be provided soon…

Use feedback contests….

Remember Pacman Dashboard!

Better individual stats

THE Review today 4:30pm

Join me at 4:30pm!

Next week ….

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Questions?

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What have we seen?
Search: as a general problem solving technique.
Knowledge Representation: rational behavior requires knowledge! Beyond databases…
Automated Planning: what plan should I execute?
mixing search + KR

Probabilities: basic tool for reasoning under uncertainty.
Bayesian Networks: knowledge representation for probabilistic reasoning.
MDP: decision making under uncertainty
Reinforcement Learning: learn environment and how to act rationally.

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Whiteboard used for reviewing…

Semantics of Bayes Nets
If we ask for P(x1, x2,…, xn) we obtain
assuming an ordering consistent with network.
By the chain rule, we have:
P(x1, x2,…, xn) =
= P(xn | xn-1, … , x1) P(xn-1 | xn-2, …, x1) … P(x1)
= P(xn | Par(xn)) P(xn-1 | Par(xn-1)) … P(x1)

Thus, the joint is recoverable using the parameters (CPTs) specified in an arbitrary BN