Course talk:CPSC522/Deep Q-Learning

From UBC Wiki

Contents

Thread titleRepliesLast modified
Critique117:41, 16 March 2018
Feedback205:44, 15 March 2018
Critique123:04, 12 March 2018

It's really a nice paper. The contents are written well. I just have some comments. You may want to explain more about the second paper and make some changes so that it's more clear what the second paper is and when you're starting to talk about that. At the first glance, I was not able to tell the second paper is about continuous control. You may also want to add some references to your figures or use pseudo code templates instead of using pictures.

I a scale of 1 to 5, where 1 means "strongly disagree" and 5 means "strongly agree" please rate and comment on the following:

  • The topic is relevant for the course. 5
  • The writing is clear and the English is good. 5
  • The page is written at an appropriate level for CPSC 522 students (where the students have diverse backgrounds). 5
  • The formalism (definitions, mathematics) was well chosen to make the page easier to understand. 5
  • The abstract is a concise and clear summary. 4
  • There were appropriate (original) examples that helped make the topic clear. 4
  • There was appropriate use of (pseudo-) code. 5
  • It had a good coverage of representations, semantics, inference and learning (as appropriate for the topic). 5
  • It is correct. 5
  • It was neither too short nor too long for the topic. 5
  • It was an appropriate unit for a page (it shouldn't be split into different topics or merged with another page). 5
  • It links to appropriate other pages in the wiki. 5
  • The references and links to external pages are well chosen. 5
  • I would recommend this page to someone who wanted to find out about the topic. 5
  • This page should be highlighted as an exemplary page for others to emulate. 5

If I was grading it out of 20, I would give it: 19

AINAZHAJIMORADLOU (talk)07:33, 14 March 2018

Thanks! My intention was to juxtapose the two DeepMind papers with criticism of Deep Reinforcement Learning. You are right, it makes it difficult to distinguish what the second paper is. I will try to transcribe the pictures into pseudo-code if time permits.

FabianNikolausTrutzRuffyVarga (talk)17:41, 16 March 2018
 

Though the article is well written but i didn't find clear boundary between two papers. This made things confusing for me as to not know the contributions of the second paper over first. Other than that the article is good.

I a scale of 1 to 5, where 1 means "strongly disagree" and 5 means "strongly agree" please rate and comment on the following:

  • The topic is relevant for the course. -5
  • The writing is clear and the English is good. 5
  • The page is written at an appropriate level for CPSC 522 students (where the students have diverse backgrounds). 5
  • The formalism (definitions, mathematics) was well chosen to make the page easier to understand. 4
  • The abstract is a concise and clear summary. 5
  • There were appropriate (original) examples that helped make the topic clear. 4
  • There was appropriate use of (pseudo-) code. 4
  • It had a good coverage of representations, semantics, inference and learning (as appropriate for the topic). 5
  • It is correct. 5
  • It was neither too short nor too long for the topic. 5
  • It was an appropriate unit for a page (it shouldn't be split into different topics or merged with another page). 5
  • It links to appropriate other pages in the wiki. 5
  • The references and links to external pages are well chosen. 5
  • I would recommend this page to someone who wanted to find out about the topic. 5
  • This page should be highlighted as an exemplary page for others to emulate. 5

If I was grading it out of 20, I would give it: 18

EktaAggarwal (talk)22:45, 12 March 2018

It made some edits, is the distinction clearer now?

FabianNikolausTrutzRuffyVarga (talk)23:04, 12 March 2018

Yes, it is.

EktaAggarwal (talk)05:44, 15 March 2018
 
 

I have nothing to say, this page is really nice.

JulinSong (talk)21:57, 12 March 2018