how to solve minesweeper in 3 minutes
play

How to solve Minesweeper In 3 minutes Steven Waterman LOOK HERE IF - PowerPoint PPT Presentation

Oct 16, 2023 •259 likes •841 views

How to solve Minesweeper In 3 minutes Steven Waterman LOOK HERE IF YOUVE PLAYED MINESWEEPER BEFORE LOOK HERE IF Basics YOU DONT KNOW WHAT MINESWEEPER IS Minesweeper Board! Rectangular! Cells! Cells can be clear or mines 1 2 1

  1. How to solve Minesweeper In 3 minutes Steven Waterman

  2. LOOK HERE IF YOU’VE PLAYED MINESWEEPER BEFORE LOOK HERE IF Basics YOU DON’T KNOW WHAT MINESWEEPER IS

  3. Minesweeper Board! Rectangular! Cells!

  4. Cells can be clear or mines 1 2 1 2 1 2 2 2 2 2 2 1 1 2 2 2 1 1 0 2 2 2 1 1 1 1 1 2 1 1 1 2 3 2 2 1 1 1 1 There is 1 mine in these 3 cells 2 2 1 2 1 1 1 2 1 2 2 1

  5. Let’s Play! 9x9 board, 15 bombs

  7. 2 mines / 2 unknowns All are mines 1 1 Can flag 0 1 0 1 0 1 2 2 0 0 0 1 0 0 0 1 0 0 0 1

  8. 0 / 2 0 / 3 None are mines None are mines 1 1 Can Clear Can Clear 0 1 0 1 0 1 2 2 0 0 0 1 0 0 0 1 0 0 0 1

  9. 1 / 1 Can Flag 1 1 1 0 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1

  10. 0 / 1 0 / 2 Can Clear Can Clear 1 1 1 0 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1

  11. Stuck :( 1 1 1 1 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  12. 1 / 5 1 / 2 1 1 1 1 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  13. 1 / 5 Contains 1 / 2 1 1 1 1 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  14. 1 / 5 1 / 2 minus 1 1 1 1 0 1 2 3 0 1 3 1-1 mines 0 1 2 2 3 5-2 cells 0 / 3 0 0 0 1 3 0 / 3 Can Clear 0 0 0 1 0 0 0 1 2

  15. 2 0 1 1 / 1 2 / 2 2 0 1 Can Flag Can Flag 1 1 1 1 2 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  16. 2 0 1 0 / 1 2 0 1 Can Clear 1 1 1 1 2 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  17. 2 0 1 0 / 1 2 2 0 1 Can Clear 1 1 1 1 2 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  18. 2 2 0 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 2 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  19. 2 2 0 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 2 0 1 2 3 0 1 3 0 1 2 2 3 0 / 1 0 0 0 1 3 Can Clear 0 0 0 1 0 0 0 1 2

  20. 2 2 0 1 1 / 5 Contains 1 / 2 2 2 0 1 1 1 1 1 2 2 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  21. 2 2 0 1 1 / 5 Contains 1 / 2 2 2 0 1 1 1 1 1 2 2 0 1 2 3 0 1 3 0 1 2 2 3 0 0 0 1 3 0 / 3 0 0 0 1 Can Clear 0 0 0 1 2

  22. 2 2 0 1 1 / 5 Contains 1 / 2 2 2 0 1 1 1 1 1 1 2 2 1 0 1 2 3 1 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  23. 2 2 0 1 1 / 5 Contains 1 / 2 2 2 0 1 1 1 1 1 1 2 2 1 0 1 2 3 1 0 1 3 0 1 2 2 3 0 0 0 1 3 0 / 3 0 0 0 1 Can Clear 0 0 0 1 2

  24. 2 2 0 1 1 / 4 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  25. 2 2 0 1 1 / 4 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 / 2 0 0 0 1 Can Clear 0 0 0 1 2

  26. 2 2 0 1 1 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  27. 2 2 0 1 1 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 / 2 0 0 0 1 Can Clear 0 0 0 1 2

  28. 2 2 0 1 1 1 2 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  29. 2 2 0 1 1 1 2 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 1 2 0 1 3 1 / 1 0 1 2 2 3 Can Flag 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  30. 2 2 0 1 1 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  31. 2 2 0 1 1 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 1 2 0 1 3 0 1 2 2 3 0 / 1 0 0 0 1 3 Can Clear 0 0 0 1 0 0 0 1 2

  32. 2 2 0 1 1 1 1 / 3 Contains 1 / 2 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  33. 2 2 0 1 1 1 0 / 1 2 2 0 1 1 1 Can Clear 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  34. 2 2 0 1 1 1 1 / 1 2 2 0 1 1 1 Can Flag 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  35. 2 2 0 1 1 1 0 / 1 2 2 0 1 1 1 Can Clear 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  36. 2 2 0 1 1 1 1 Stuck :( 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  37. Let’s Play! 9x9 board, 15 bombs

  38. Let’s Play! 9x9 board, 15 bombs

  39. Let’s Play! 9x9 board, 15 bombs

  40. 15 15 15 bombs bombs bombs Let’s Play! 15 9x9 board, 15 bombs 15 bombs bombs

  41. 2 2 0 1 1 1 1 15 / 81 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  42. 2 2 0 1 1 1 1 7 / 20 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  43. 2 2 0 1 1 1 1 6 / 18 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 1 0 0 0 1 2

  44. 2 2 0 1 1 1 1 5 / 18 1 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  45. 2 2 0 1 1 1 1 4 / 18 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 1 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  46. 2 2 0 1 1 1 1 0 / 18 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 4 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  47. 2 2 0 1 1 1 1 0 / 9 2 2 0 1 1 1 Can Clear 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 0 0 0 1 0 0 0 1 2

  48. 2 2 0 1 1 1 1 2 / 2 2 2 0 1 1 1 Can Flag 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 1 0 0

  49. 2 2 0 1 1 1 1 0 / 1 2 2 0 1 1 1 Can Clear 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 1 0 0

  50. 2 2 0 1 1 1 1 2 / 2 2 2 0 1 1 1 Can Flag 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 1 0 0

  51. 2 2 0 1 1 1 1 0 / 1 2 2 0 1 1 1 Can Clear 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 1 0 0

  52. 2 2 0 1 1 1 1 1 / 1 2 2 0 1 1 1 Can Flag 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 1 0 0

  53. 2 2 0 1 1 1 1 0 / 1 2 2 0 1 1 1 Can Clear 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 1 0 0

  54. ...What now? 2 2 0 1 1 1 1 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 It’s time for... 0 1 2 3 2 1 2 0 1 3 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 2 1 0 0

  56. Guessing 2 2 0 1 1 1 1 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 0 1 2 3 2 1 2 0 1 3 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 2 1 0 0

  57. 2 2 0 1 1 1 1 2 2 0 1 1 1 1 1 1 1 2 2 1 1 1 :( 0 1 2 3 2 1 2 0 1 3 3 4 0 1 2 2 3 4 0 0 0 1 3 3 2 2 0 0 0 1 2 0 0 0 0 0 1 2 2 1 0 0

  58. ( bad solver code on github @stevenwaterman) Next time: ● Constraint Reduction ● Inexact Constraints ● Proof of Completeness ● How to actually implement it ● How to do it without taking exponential time So get excited for How to solve minesweeper in a series of 20 hour-long lectures!

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Threads More algorithm efficiency analysis, Big-Oh Work on Minesweeper See the nine

Threads More algorithm efficiency analysis, Big-Oh Work on Minesweeper See the nine

Threads More algorithm efficiency analysis, Big-Oh Work on Minesweeper See the nine announcements in the email message that I sent you yesterday afternoon. By now, everyone should know how to submit how to submit files in AFS and to SVN

590 views • 33 slides
Become A Guru How T o Solve A Memory Leak In Under 10 Minutes Confidential - do not distribute

Become A Guru How T o Solve A Memory Leak In Under 10 Minutes Confidential - do not distribute

Become A Guru How T o Solve A Memory Leak In Under 10 Minutes Confidential - do not distribute What You Will Learn A methodology for approaching memory leaks Understanding the generational heap Understanding generational aging to

667 views • 33 slides
Project Minesweeper Andreas, Evy, Martin, Rebekka & Siripong Basic idea Possibility to

Project Minesweeper Andreas, Evy, Martin, Rebekka & Siripong Basic idea Possibility to

Project Minesweeper Andreas, Evy, Martin, Rebekka & Siripong Basic idea Possibility to reserve a group room From this Anarchy To this Democracy Transcending the traditional role of the library User-centered design Observations

485 views • 17 slides
Mood. Aim 7.4: How do we solve Regents style rational equation problems? HW: DeltaMath DoNow

Mood. Aim 7.4: How do we solve Regents style rational equation problems? HW: DeltaMath DoNow

AIM (7.4) : How do we solve Regents style rational equation problems? Alert! Take two minutes to get your Notebooks, Calculators, & Student Orgzniers before we begin today's lesson. Alert! Mood. Aim 7.4: How do we solve Regents style

304 views • 17 slides
Data Structure Definition Array implementation Begin Data Structures Grand Tour Minesweeper

Data Structure Definition Array implementation Begin Data Structures Grand Tour Minesweeper

Data Structure Definition Array implementation Begin Data Structures Grand Tour Minesweeper team/team members peer Minesweeper team/team members peer review review survey (on ANGEL) survey (on ANGEL) due by 5 PM Today. Home || Course

327 views • 17 slides
Generic types Measuring Efficiency Minesweeper start-up Grader comments for JUnit and

Generic types Measuring Efficiency Minesweeper start-up Grader comments for JUnit and

Generic types Measuring Efficiency Minesweeper start-up Grader comments for JUnit and BigRational assignments should be in your repository. There seems to be a problem there with JUnit. Should be resolved this afternoon Details about

230 views • 10 slides
MineSweeper: An In-depth Look into Drive-by Mining and its Defense Veelasha Moonsamy Utrecht

MineSweeper: An In-depth Look into Drive-by Mining and its Defense Veelasha Moonsamy Utrecht

MineSweeper: An In-depth Look into Drive-by Mining and its Defense Veelasha Moonsamy Utrecht University, The Netherlands 28 August 2018 University of Adelaide, Australia Utrecht University, The Netherlands 2 Acknowledgment Joint

874 views • 61 slides
From days to minutes, from From days to minutes, from minutes to milliseconds with minutes to

From days to minutes, from From days to minutes, from minutes to milliseconds with minutes to

From days to minutes, from From days to minutes, from minutes to milliseconds with minutes to milliseconds with SQLAlchemy SQLAlchemy Leonardo Rochael Almeida 10-July-2019 Hi, Im Leo. Im a Tech Lead at Geru. Im here today to talk

739 views • 54 slides
Take two minutes to get your Packet, Folder, and Signals before we begin today's lesson. Aim 2.5:

Take two minutes to get your Packet, Folder, and Signals before we begin today's lesson. Aim 2.5:

AIM(2.5): How do we create and solve a linear inequality from a scenario? Take two minutes to get your Packet, Folder, and Signals before we begin today's lesson. Aim 2.5: How do we create and solve a linear inequality from a scenario? HW:

247 views • 14 slides
Together we can solve problems that are too big for any one organization to solve alone Eastern

Together we can solve problems that are too big for any one organization to solve alone Eastern

Together we can solve problems that are too big for any one organization to solve alone Eastern Mojave LCD Coordinating Team Desert LCC Team: Genevieve Johnson Bureau of Reclamation Matt Grabau US Fish and Wildlife Service

416 views • 19 slides
N ew D eve l o p m e n t s i n P a r t o n S h owe r s P. S k a n d s ( C E R N ) Goal: solve

N ew D eve l o p m e n t s i n P a r t o n S h owe r s P. S k a n d s ( C E R N ) Goal: solve

N ew D eve l o p m e n t s i n P a r t o n S h owe r s P. S k a n d s ( C E R N ) Goal: solve this (Request to experiments: solve this) Fields Hits Symmetries 0100110 Amplitudes Acceptance Theory Experiment Monte Carlo Feedback Loop

684 views • 35 slides
Approximation Algorithms Q. Suppose I need to solve an NP-hard problem. What should I do? A.

Approximation Algorithms Q. Suppose I need to solve an NP-hard problem. What should I do? A.

Approximation Algorithms Q. Suppose I need to solve an NP-hard problem. What should I do? A. Theory says you're unlikely to find a poly-time algorithm. Must sacrifice one of three desired features. Solve problem to optimality. Solve

247 views • 20 slides
DES in 10 minutes DES in 7 minutes, Balrog in 3 minutes Megan Splettstoesser Fermilab New

DES in 10 minutes DES in 7 minutes, Balrog in 3 minutes Megan Splettstoesser Fermilab New

FERMILAB-SLIDES-18-099-E DES in 10 minutes DES in 7 minutes, Balrog in 3 minutes Megan Splettstoesser Fermilab New Perspectives June 18, 2018 This document was prepared by [DES Collaboration] using the resources of the Fermi National

506 views • 28 slides
Class Outline: Anterior Anatomy 5 minutes Breath of Arrival and Attendance 5 minutes

Class Outline: Anterior Anatomy 5 minutes Breath of Arrival and Attendance 5 minutes

Class Outline: Anterior Anatomy 5 minutes Breath of Arrival and Attendance 5 minutes Howdy Partner 35 minutes Anterior Anatomy using Power Point Presentation 5 minutes Overview of skeletal segments 5 minutes Quick drawing of

776 views • 55 slides
Class Outline: Posterior Anatomy 5 minutes Breath of Arrival and Attendance 5 minutes

Class Outline: Posterior Anatomy 5 minutes Breath of Arrival and Attendance 5 minutes

Class Outline: Posterior Anatomy 5 minutes Breath of Arrival and Attendance 5 minutes Howdy Partner 35 minutes Posterior Anatomy using Power Point Presentation 5 minutes Overview of skeletal segments 5 minutes Quick drawing

860 views • 63 slides
Breakout Group Reinforcement Learning F ABIAN R UEHLE (U NIVERSITY OF O XFORD ) String_Data 2017,

Breakout Group Reinforcement Learning F ABIAN R UEHLE (U NIVERSITY OF O XFORD ) String_Data 2017,

Breakout Group Reinforcement Learning F ABIAN R UEHLE (U NIVERSITY OF O XFORD ) String_Data 2017, Boston 12/01/2017 Outline Theoretical introduction ( 30 minutes ) Discussion of code ( 30 minutes ) Solve version of grid world with

483 views • 15 slides
NDN protocol development: status of reference implementa5ons,

NDN protocol development: status of reference implementa5ons,

NDN protocol development: status of reference implementa5ons, suppor5ng so8ware releases, open architecture research issues Alex Afanasyev University of California,

202 views • 18 slides
Introduc>on TREC 2012 Context Sugges>on track operates on

Introduc>on TREC 2012 Context Sugges>on track operates on

11/12/12 (Not Too) Personalized Learning to Rank for Contextual Sugges>on Andrew Yates 1 , Dave DeBoer 1 , Grace Hui Yang 1 , Nazli Goharian 1 , Steve

667 views • 14 slides
Building Disciples Through Service Webinar with Joan Weber and Susan Searle Sponsored By

Building Disciples Through Service Webinar with Joan Weber and Susan Searle Sponsored By

Building Disciples Through Service Webinar with Joan Weber and Susan Searle Sponsored By Called to Be Missionary Disciples Following Jesus demands a good dose of courage, a readiness to trade in the sofa for a pair of walking shoes and

752 views • 37 slides
Public Service Mutuals: A good option for Library Services? Department for Culture, Media &

Public Service Mutuals: A good option for Library Services? Department for Culture, Media &

Public Service Mutuals: A good option for Library Services? Department for Culture, Media & Sport Where do we start from? Significant programme from 2010 - 2015 A small number of library services have spun out Recent

240 views • 8 slides
Class 2 Topics Stages & Phases of Labor 2nd Stage Labor/Pushing Labor positions

Class 2 Topics Stages & Phases of Labor 2nd Stage Labor/Pushing Labor positions

5/15/2020 Welcome! Childbirth Preparation 4 Week Series Week 2 Class 2 Topics Stages & Phases of Labor 2nd Stage Labor/Pushing Labor positions Birth Video Coping Skills Your Hospital Stay Arrival at Hospital o

549 views • 11 slides
SI425 : NLP Set 5 Nave Bayes Classification Motivation We want to predict something .

SI425 : NLP Set 5 Nave Bayes Classification Motivation We want to predict something .

SI425 : NLP Set 5 Nave Bayes Classification Motivation We want to predict something . We have some text related to this something. something = target label Y text = text features X Given X, what is the most probable Y?

1.25k views • 15 slides
RPKI A quick configuration intro Massimiliano Stucchi | 19th January 2016 | UKNOF33 RPKI

RPKI A quick configuration intro Massimiliano Stucchi | 19th January 2016 | UKNOF33 RPKI

RPKI A quick configuration intro Massimiliano Stucchi | 19th January 2016 | UKNOF33 RPKI Overview Massimiliano Stucchi - RIPE NCC | 19th January 2016 | UKNOF33 2 Simply put 3 parts - Create certificates - Install/run validator -

562 views • 17 slides
Game Theory - Lecture #12 Outline: Randomized actions vNM & Bernoulli payoff functions

Game Theory - Lecture #12 Outline: Randomized actions vNM & Bernoulli payoff functions

Game Theory - Lecture #12 Outline: Randomized actions vNM & Bernoulli payoff functions Mixed strategies & Nash equilibrium Hawk/Dove & Mixed strategies Randomized action profiles Original strategic setup: Set of

361 views • 10 slides

More recommend