Thanks for this interesting content. Where can we get this training visualization?

who is here from cmpt 310 sfu

All 7 of us actually studying this not from UCB

Yunsheng is smurfing in this course

Nice lecture . Thanks!

Moto of life - Maximise Expected Utiity

I really enjoyed this class. Thank you

Do they do the JoJ in this lecture? I heard they do the JoJ in this lecture.

Hey guys, Computer Science here!

00:00 Setup [no content] 02:57 Announcements [outdated] 07:50 Recap: Search 15:54 Uninformed Search 18:56 Heuristics 25:40 Greedy Search 31:56 A* Search 39:34 Admissibility of Heuristics 44:09 Optimality of A* 49:09 Break [no content] 54:17 A* Q&A 1:01:15 Properties of A* 1:06:45 Creating Heuristics 1:14:08 Graph Search 1:18:53 Consistency of Heuristics 1:22:33 End [no content]"

Done > Fixed the bug in upper timestamps: 00:00 Setup [no content] 03:33 Announcements [outdated] 07:31 AI Research at Berkeley [no content] 09:34 Reflex Agents 14:46 Planning Agents 17:53 Search Problem Definition 22:23 State Spaces 32:58 State Space Quiz Answer 38:04 State Space Graphs and Search Trees 43:19 Tree Search 51:07 Break [no content] 53:10 Depth-First Search 00:43 Breadth-First Search 1:03:56 DFS vs. BFS 1:08:21 Iterative Deepening 1:10:57 Uniform-Cost Search 1:18:41 Implementing Search 1:21:24 End [no content]"

super

Starts at 3:55

Great lecture

31:15 what happened in washington 2018 september?

Listening to this in 2023 and thinking of Theranos teehee

he is the GOAT

Best lecturer ever

Excellent class !

I just love him. A true educator。

does anyone know that which app is the teacher used with BN demo at 1:23:00

58:00 I thought you square it so larger errors have a bigger proportion than smaller errors

More lecture slides should include cartoon images.

thank you so much! so clear so helpful!! my AI course lecturer is using you slides, but he is teaching us the sh*t.

1:08:52

The graph in 1:18:49. I changed the h(A)=2 to make the heuristic consistent but the solution is still S-B-C-G in A* graph search because B(1+1)<A(1+2). So C's parent is still B.

I appreciate whoever made the little robot images on the presentation slides, they convey emotion quite well without being distracting.

sad grad students HMM XD

At 54:00. Anyone watching this in 2023 and thinking, ChatGPT can do that. It's amazing how fast tech is growing.

is there any more information about project 3 - the crawler

苟利国家生死以，岂因祸福避趋之

amazing lecture

It's from 2018 but already so outdated on things like "AI can't have a successful conversation with someone for over an hour". Just showcases how rapidly the industry is still evolving.

Topoic: Adversarial Search

Topic: Adverserial Search

Topic: CSP + Local Search

Topic: CSP

Excellent lecture. In fact, I'd do it all over again.

Watched this at 90% speed, thank you

In case you are wondering, my teacher is using all of your slides, projects and notes for his lecture. And I understand nothing from him. But this video made everything clear for me. And I am paying for my school. But this is free and better. But I need the degree. So I need to pay for the school like an idiot. I feel like if you don't publish never version of this topic he will be teaching the same things till 2038.

Lisa Queries

He looks like Steve Jobs!

I can finally beat minesweeper!

for the traffic example at 28:22 . maybe robot holds an Umbrella means it's been raining long time before robot goes out, and this might means more traffic and changes our probability, because know P(T | R, U) != P(T | R) != P(T | U) so it's no more conditionally independent (10mins raining varies to 1 hour raining in a traffic model)

I thought I was finally done with pacman... sad sad

I am wondering what was the avenger's joke that he had in his mind.

Lecture starts at 2:00

Lecture starts at 4:30

Can't hear the video playing in the classroom, "the thinking machine". Is there a transcript or another link for it?

Lecture starts at 3:25