Professor Bryce
Professor Bryce
  • Видео 131
  • Просмотров 274 867
Data Structures for Deviation Payoffs (AAMAS Talk)
Paper abstract:
We present new data structures for representing symmetric normal-form games. These data structures are optimized for efficiently computing the expected utility of each unilateral pure-strategy deviation from a symmetric mixed-strategy profile. The cumulative effect of numerous incremental innovations is a dramatic speedup in the computation of symmetric mixed-strategy Nash equilibria, making it practical to represent and solve games with dozens to hundreds of players. These data structures naturally extend to role-symmetric and action-graph games with similar benefits.
Paper link: arxiv.org/abs/2302.13232
Julia library with the paper's experiments: github.com/Davidson-Game-Th...
Просмотров: 614

Видео

Counterfactual Regret Minimization (AGT 26)
Просмотров 10 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 14 - Wednesday.
Sequential (and Perfect Bayesian) Equilibrium (AGT 25)
Просмотров 4 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 14 - Monday.
Subgame Perfection and Backwards Induction (AGT 24)
Просмотров 1,2 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 13 - Wednesday.
Extensive Form Games (AGT 23)
Просмотров 978Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 13 - Monday.
Action-Graph Games (AGT 22)
Просмотров 357Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 12 - Wednesday.
Congestion Games (AGT 21)
Просмотров 1 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 12 - Monday.
Data Structures for Symmetric Games (AGT 20)
Просмотров 331Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 11 - Wednesday. This video covers ideas from my recent paper: arxiv.org/abs/2302.13232
Gradient Descent for Nash (AGT 19)
Просмотров 445Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 11 - Monday.
Replicator Dynamics (AGT 18)
Просмотров 1,6 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 10 - Wednesday.
Fictitious Play and Regret Matching (AGT 17)
Просмотров 2,2 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 10 - Monday.
Complexity of Nash: PPAD (AGT 16)
Просмотров 579Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 9 - Wednesday.
Reductions and Why Zero Sum only Helps with Two Players (AGT 15)
Просмотров 336Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 9 - Monday.
Finding (Coarse) Correlated Equilibria with Linear Programming (AGT 14)
Просмотров 2 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 7 - Wednesday.
Finding Zero Sum Nash Equilibria with Linear Programming (AGT 13)
Просмотров 1,1 тыс.Год назад
Davidson CSC 383: Algorithmic Game Theory, S23. Week 7 - Monday.
Nash Algorithm Starting Points (AGT 12)
Просмотров 438Год назад
Nash Algorithm Starting Points (AGT 12)
Symmetric Games and Sperners Lemma (AGT 11)
Просмотров 628Год назад
Symmetric Games and Sperners Lemma (AGT 11)
Nash's Theorem: Every Game has an Equilibrium (AGT 10)
Просмотров 1,9 тыс.Год назад
Nash's Theorem: Every Game has an Equilibrium (AGT 10)
Equilibria with Pre-Commitment: Stackelberg & Coarse Correlated (AGT 09)
Просмотров 661Год назад
Equilibria with Pre-Commitment: Stackelberg & Coarse Correlated (AGT 09)
Nash Refinements: Trembling Hand and Evolutionary Stability (AGT 08)
Просмотров 1,9 тыс.Год назад
Nash Refinements: Trembling Hand and Evolutionary Stability (AGT 08)
Nash Approximation: ε-Equilibria (AGT 07)
Просмотров 759Год назад
Nash Approximation: ε-Equilibria (AGT 07)
Predicting Joint Behavior with Correlated Equilibria (AGT 06)
Просмотров 1,9 тыс.Год назад
Predicting Joint Behavior with Correlated Equilibria (AGT 06)
Predicting Strategies with Mixed Nash Equilibria (AGT 05)
Просмотров 821Год назад
Predicting Strategies with Mixed Nash Equilibria (AGT 05)
Predicting Actions with Dominance and Pure-Nash (AGT 04)
Просмотров 7542 года назад
Predicting Actions with Dominance and Pure-Nash (AGT 04)
Preference Aggregation (AGT 03)
Просмотров 9842 года назад
Preference Aggregation (AGT 03)
Welcome and Setup (Comp. Org. 01)
Просмотров 1,3 тыс.2 года назад
Welcome and Setup (Comp. Org. 01)
Von Neumann-Morgenstern Utility (AGT 02)
Просмотров 2,9 тыс.2 года назад
Von Neumann-Morgenstern Utility (AGT 02)
Game Theory Intro (AGT 01)
Просмотров 4,9 тыс.2 года назад
Game Theory Intro (AGT 01)
Approximation Algorithms (Algorithms 25)
Просмотров 4,9 тыс.2 года назад
Approximation Algorithms (Algorithms 25)
AlphaGo & AlphaGo Zero (DL 24)
Просмотров 8032 года назад
AlphaGo & AlphaGo Zero (DL 24)

Комментарии

  • @BartDriessen92
    @BartDriessen92 2 дня назад

    Thank you so much for putting this out there, this is incredibly well-explained!

  • @ahmad2892
    @ahmad2892 7 дней назад

    Amazing explanation

  • @qubit966
    @qubit966 8 дней назад

    why do we use the derivative?

  • @qubit966
    @qubit966 8 дней назад

    very well done and informative.

  • @zanubiadepasquale
    @zanubiadepasquale 11 дней назад

    thank you so much, extremely useful, very clear!!

  • @27Dionysis
    @27Dionysis 12 дней назад

    Thank you, this is the best example of a Stack Diagram I've seen.

  • @brunotrotti6942
    @brunotrotti6942 13 дней назад

    Remarkable work, very good video format.

  • @SadikHKhan
    @SadikHKhan 16 дней назад

    why are these videos so underrated???

  • @storiesbeneaththesurface1942
    @storiesbeneaththesurface1942 17 дней назад

    best explanation

  • @khaliliskarous2225
    @khaliliskarous2225 17 дней назад

    Best explanation I've seen for skip connections. Thanks!

  • @maryamatabati5812
    @maryamatabati5812 17 дней назад

    You just explained it perfect! Thank you!

  • @tinymints3134
    @tinymints3134 18 дней назад

    that was UNBELIEVABLY clear and understandable. THANK YOU

  • @nathanielmatora5575
    @nathanielmatora5575 18 дней назад

    Holy shi dude I never really comment but this video is freakin good your explanations are on point and u broke down the architecture superbly

  • @tuzinshow
    @tuzinshow Месяц назад

    i love you mr. bryce!

  • @priyanshpal4412
    @priyanshpal4412 Месяц назад

    Thank you professor. The best explanation, he includes influence of random weights on forward propagation.

  • @dapphari007
    @dapphari007 Месяц назад

    Anna university

  • @tarungrover9415
    @tarungrover9415 Месяц назад

    holy moly, this was a really good explanation!

  • @portobellomushroom5764
    @portobellomushroom5764 Месяц назад

    Very very very clever reduction

  • @ShreyaShivanandPandey
    @ShreyaShivanandPandey Месяц назад

    professor Bryce , youre the GOAT!

  • @huyngo9507
    @huyngo9507 Месяц назад

    Thank you for such a clear explanation

  • @chloehuang3554
    @chloehuang3554 Месяц назад

    Thank you for a such clear video!!! Life saving!

  • @DevanshShahOrigami
    @DevanshShahOrigami Месяц назад

    thanks a lot sir! really well explained!

  • @saltykheera
    @saltykheera Месяц назад

    sir you deserves the most slopiest bj from my side gawk gawk thank you very much

  • @crowsnest6753
    @crowsnest6753 2 месяца назад

    Thank you for the clear and concise explanation.

  • @akashnayak3752
    @akashnayak3752 2 месяца назад

    The best explanation ever. Thank you professor

  • @juandaviduribe8267
    @juandaviduribe8267 2 месяца назад

    Great video

  • @Aman-xo4yx
    @Aman-xo4yx 2 месяца назад

    So perfect

  • @MarilynHazlett
    @MarilynHazlett 2 месяца назад

    Thank you for this great video. Why don't you use Kakutani's FPT? So we don't have to worry about the adv fnc being a one-to-one mapping?

  • @ShreyaShivanandPandey
    @ShreyaShivanandPandey 2 месяца назад

    geniusssssssssssssssss , my heart is so full after watching this video

  • @GisleGaren
    @GisleGaren 2 месяца назад

    I can't remember the last time I commented on a youtube video as it was much too long ago, but I just had to because your videos on deeplearning are CRIMINALLY underrated. I have yet to find another resource that explains ResNet so intuitively as you break down each concepts to laymen terms and you take your time explaining them. You have an amazing way of explaining concepts and I sincerely hope your videos get all the recognition they deserve!

  • @yunusisah9244
    @yunusisah9244 2 месяца назад

    Good day, am having difficulties understanding how to point out the independent set and vertex cover from a graph

  • @cliveblackwell2316
    @cliveblackwell2316 2 месяца назад

    @zachrayman7879 is correct that the cell (a,cf) should be (2,2). Reply is also correct in that in the subgame after player 1 plays b player 2 moves e so (a,cf) is not subgame perfect

  • @abdulsamadibrahim9084
    @abdulsamadibrahim9084 2 месяца назад

    I have been stuck at 6:56, why are the slack finish times: 1, 11, 15 and 17? Could you please explain the calculations behind that

  • @andychess
    @andychess 2 месяца назад

    Great explanation, it helped me a lot. Thank you for taking the time to make this video!

  • @Robelseyoum-s2l
    @Robelseyoum-s2l 2 месяца назад

    Wow amazing tutorial. Thanks ❤

  • @ali57555
    @ali57555 2 месяца назад

    Thank you very much, This is great. I'm watching this again and still super helpful. So delta is actually the upstream gradient, right? I only think that it would be nice to mention what is a computation graph, but otherwise, super helpful.

  • @angelobruch
    @angelobruch 2 месяца назад

    Thanks, you are the best ❤

  • @lyh4687
    @lyh4687 3 месяца назад

    great tutorial!

  • @hehesexyboi
    @hehesexyboi 3 месяца назад

    Bro is underrated asf

  • @BeingWalters
    @BeingWalters 3 месяца назад

    very nice 🎉

  • @itmesneha
    @itmesneha 3 месяца назад

    thank you so so much for this video!

  • @eeThial5
    @eeThial5 3 месяца назад

    Wow, so clear! That was stellar, thank you!

  • @tiananmentank-pj7sf
    @tiananmentank-pj7sf 3 месяца назад

    A true legend

  • @Eddie-m7v
    @Eddie-m7v 3 месяца назад

    shouldn't folding have a utility or expected value of zero. since no money goes into the pot how can it return -1 in value?

  • @محمدرضااحمدی-ل1د
    @محمدرضااحمدی-ل1د 3 месяца назад

    thanks. Sorry but the video you mentioned in the last seconds of this video in not yet uploaded(video about stability proof)

  • @noumanahmad308
    @noumanahmad308 3 месяца назад

    That was amazing! So clear and concise explanation. Thanks!

  • @mohamedsidibe9876
    @mohamedsidibe9876 3 месяца назад

    Thank you for your good explanation, helped me a lot on my deep understanding journey of all these mechanims 😊

  • @kevinkevin7900
    @kevinkevin7900 4 месяца назад

    AMAZING!!

  • @sufiyanshaikh7735
    @sufiyanshaikh7735 4 месяца назад

    In this example iI think Sj >= Fgi because if Sj is smaller then there is a conflict in task and the task is not compatible instead the Si should be after the finish time of last request