1. The Scientific Community Game: Education and Innovation Through Survival in a Virtual World of Claims Karl Lieberherr Northeastern University College of Computer and Information Science Boston, MA joint work with Ahmed Abdelmeged and Bryan Chadwick Karl Lieberherr Northeastern University College of Computer and Information Science Boston, MA joint work with Ahmed Abdelmeged and Bryan Chadwick Supported by Novartis

2. Why Scientific Community Game (SCG) … motives in academic publishing: – desire for recognition and respect from the people one regards as peers, – desire to have impact (on conclusions being reached, on the development of the discipline, etc.), and – desire to participate in significant knowledge- building discourse. e.g., Scardamalia, M., & Bereiter, C. (1994) Intro SCG2

3. SCG is Bio-inspired Virtual world of scholars based on natural selection – propose, oppose (refute and strengthen) claims – maximize reputation, weak scholars are removed. Turn problem-solving software into virtual organisms that fend for themselves and survive in a virtual world inhabited by virtual organisms created by your peers. Intro SCG3

4. SCG is a web-based implementation of Karl Popper’s science ideas One of the greatest philosophers of science of the 20th century.philosophers of science Falsifiability or refutability is the logical possibility that an assertion could be shown false by a particular observation or physical experiment. Error elimination (refutation), performs a similar function for science that natural selection performs for biological evolution.natural selectionbiological evolution Intro SCG4 from Wikipedia

5. Comparison Karl Popper: Conjectures and Refutations Scientific Community Game: Claims and Refutations Intro SCG5

6. Recognition in SCG Scholars build their reputation by proposing and opposing claims, by defending their own claims and refuting or strengthening the claims of others. The higher their reputation, the more recognition. Intro SCG6

7. Impact in SCG Second-order environment – what one scholar does in adapting, changes the environment so that others must readapt. Developing novel techniques to find superior solutions, challenges others to catch up. Intro SCG7

8. Knowledge-Building Discourse in SCG Communication or debate. Refutation protocol defines the structure of the debate and who wins. Claims are defined through a refutation protocol. Knowledge-building: – claims that have been defended predominantly are candidates for truth – claims that have been refuted predominantly are probably false. Intro SCG8

9. Goals of SCG Put knowledge-building discourse on the web giving participants the option to gain recognition and to have impact. Focus the discourse through precise definition of claims with refutation protocols. Make knowledge building discourse fun and educational from the high school to the advanced research level. Intro SCG9 SCG = Scientific Community Game = Specker Challenge Game

10. What do we mean by science? Science consists of the formulation and testing of hypotheses based on observational evidence. Ours: Science consists of the formulation and testing of constructive claims based on observational evidence. Construction is computable. Intro SCG10

11. What do we mean by Scientific Method Hypothetico-deductive method: Formulate a hypothesis in a form that could conceivably be falsified by a test on observable data. Ours: Formulate a constructive claim in a form that could conceivably be falsified by a test using a protocol. The refutation protocol is part of the claim to make very explicit when refutation is successful. Intro SCG11

12. SCG claim examples SCG Claim – AlgorithmicClaim solve problems of kind D with quality q and resource r have polynomial time algorithm to solve problems of kind D with quality q – MathematicalClaim for all x in X exists y in Y: predicate(x,y) – SoftwareClaim solve problems of kind D with maintainability m you cannot break into a system of kind D using resource r

13. SCG claim examples – FinancialClaim if you pay me k dollars (option premium) today, I will promise to buy q shares of stock S up to day d at price p (strike price). Purpose: insurance. – ExperimentalClaim If I am given raw materials x in X, I can produce product y in Y of quality q and using resources at most r.

14. Intro SCG14 Tartaglia against Fior 1535 Tartaglia was famed for his algebraic solution of cubic equations which was published in Cardan's Ars Magna.

15. Outline Introduction – Popper Science, Renaissance History: Tartaglia and Fior Definition of SCG – Example (Highest safe rung) Applications: Teaching, Software Development, Research Claims with secrets and other protocol variants Output of SCG, Equilibrium Advantages and Disadvantages Conclusions Intro SCG15

16. Definition of SCG: Domain Problem: Set Solution: Set valid: relation(Problem, Solution) quality: function(Problem, Solution)->[0..1] 16Intro SCG

17. Claim(Domain) Problems: Powerset(Domain.Problem) q: Quality = [0,1] r: Resource = N + = positive integer Alice claims to have a technique to solve problems in Problems with at least quality q and using at most resources r. 17Intro SCG makes predictions about the future

18. Implied Protocol of Claim(Domain) Alice claims (problems,q,r), Bob refutes Bob provides problem prob in Claim.Problems. Alice solves problem prob providing sol in Domain.Solution. check: valid(prob,sol) and quality(prob,sol)>=q and sol.resource<=r. sol.resource returns Alice’ resource consumption to solve problem prob. 18Intro SCG Karl Popper: Only hypotheses capable of clashing with observation reports are allowed to count as scientific.

19. Claim Problems: subset of problems quality in [0,1] Intro SCG19 0 1 quality (how well problems in Problems can be solved)

20. Claim Intro SCG20 0 1 quality strengthening correct valuation over strengthening

21. Bio-inspired computing: Virtual World of SCG-Avatar SCG-Avatar (Claim(Domain)) – State: Reputation = positive rational number – Activity propose new claims oppose claims of others – refute claim(Problems, q, r) – strengthen claim(Problems, q’, r’), q’>q or r’<r Reputation gain: refute others’ claims and defend own claims (counter refutation attempts) Reputation loss: unsuccessful refutation of other’s claim and refutation of own claims 21Intro SCG

22. Tournament 1.round-robin 2.Swiss-style 3.elimination 1.single 2.double 22Intro SCG

23. Summary of SCG Definitions Domain Problem Solution valid(Problem, Solution) quality(Problem, Solution) → [0,1] 23Intro SCG Claim(Domain) Problems: PowerSet(Domain.Problem) q: Quality = [0,1] r: Resource = N + Rules of the Scientific Community: propose and oppose, be an active scholar, rules for reputation accumulation. Tournaments

24. Highest Safe Rung You are doing stress-testing on various models of glass jars to determine the height from which they can be dropped and still not break. The setup for this experiment, on a particular type of jar, is as follows. Intro SCG24

25. Highest Safe Rung Only two identical bottles to determine highest safe rung Alice Bob 25Intro SCG You have a ladder with n rungs, and you want to find the highest rung from which you can drop a copy of the jar and not have it break. We call this the highest safe rung. You have a fixed ``budget'' of k > 0 jars.

26. Highest Safe Rung Only two identical bottles to determine highest safe rung HSR(9,2) ≤ 4 I doubt it: refutation attempt! Alice Bob Alice constructs decision tree T of depth 4 and gives it to Bob. He checks whether T is valid. Bob wins if he finds a flaw. 26Intro SCG

27. 3 1 0 6 12 4 3 5 9 9 7 6 87 2 4 5 8 x yz yes no u highest safe rung Highest Safe Rung Decision Tree HSR(10,2)=5 27Intro SCG

28. Formal: HSR Domain: – Problem: (n,k), k <= n. – Solution: Decision tree to determine highest safe rung. – quality(problem, solution): depth of decision tree / number of rungs – valid(problem, solution): at most k left branches,... 28Intro SCG

29. Formal: HSR Claim(Domain): – Alice claims ({(25,2)},9/25,5 seconds) {(25,2)}: set of problems (singleton) 9/25: quality 5 seconds: resource Refutation Protocol: – Bob refutes: only one problem: (25,2) – Alice: solves problem by providing decision tree t. – predicate: t is a valid decision tree for (25,2) of depth 9 Intro SCG29

30. SCG(HSR) Karl Lieberherr 9/15/2015SCG(HSR)30

31. Overview Showing Scientific Community game in action as a board game. Want to play the game in class. 9/15/2015SCG(HSR)31

32. Highest Safe Rung You are doing stress-testing on various models of glass jars to determine the height from which they can be dropped and still not break. The setup for this experiment, on a particular type of jar, is as follows. SCG(HSR)329/15/2015

33. Highest Safe Rung Only two identical bottles to determine highest safe rung (k=2) Alice Bob 33SCG(HSR) You have a ladder with n rungs, and you want to find the highest rung from which you can drop a copy of the jar and not have it break. We call this the highest safe rung. You have a fixed ``budget'' of k > 0 jars. 9/15/2015

34. Highest Safe Rung Only two identical bottles to determine highest safe rung HSR(9,2) ≤ 4 I doubt it: refutation attempt! Alice Bob Alice constructs decision tree T of depth 4 and gives it to Bob. He checks whether T is valid. Bob wins if he finds a flaw. 34SCG(HSR)9/15/2015

35. SCG Scenario Interactions between scholars Alice and Bob. Admin Nina gives grade to performance of Alice and Bob. 9/15/201535SCG(HSR)

36. HSR(n,k) ≤ q There exists a valid decision tree DT-HSR(n,k) of depth q to solve HSR(n,k) so that for all ladders with n rungs and for all secret rungs s, the decision tree DT-HSR(n,k) correctly identifies s. 9/15/201536SCG(HSR)

37. 1 0 1 3 2 x yz yes no u highest safe rung 37 2 3 depth is 3 Linear Search: HSR(4,1)=3 9/15/2015SCG(HSR)

38. 2 0 1 3 x yz yes no u highest safe rung 38 2 3 Binary Search: HSR(4,2)=2 1 9/15/2015SCG(HSR)

39. Pos. HSR Use Case: HSR(n,k) <= q Name: HSR Participating actors: Alice, Bob and Nina. Entry condition: n,k,q are given; k<=n, q<=n, refuter defined: Bob. Flow of events 9/15/201539SCG(HSR)

40. Pos. HSR Use Case (continued) Flow of events – Alice claims HSR(n,k)<=q. – Bob tries to refute. Bob asks for program/algorithm for (n,k) (ProvideProblem). – Alice provides program/algorithm (SolveProblem). – Bob/Nina check correctness of program/algorithm. – Nina gives grade based on whether program/algorithm is correct and of predicted quality. 9/15/201540SCG(HSR)

41. Pos. HSR Use Case (continued) Exit condition: winner and loser are determined. Quality requirements: programming language, computational model: decision tree 9/15/201541SCG(HSR)

42. Neg. HSR Use Case: HSR(n,k) > q Name: HSR-neg Participating actors: Alice, Bob and Nina. Entry condition: n,k,q are given; k<=n, q<=n, refuter defined: Bob. Flow of events 9/15/201542SCG(HSR)

43. Neg. HSR Use Case (continued) Flow of events – Alice claims HSR(n,k)>q. – Bob tries to refute. Alice asks for program/algorithm for (n,k) (ProvideProblem). – Bob provides program/algorithm (SolveProblem). – Alice/Nina check correctness of program/algorithm. If depth of decision tree is <= q, refutation is successful. – Nina gives grade based on whether program/algorithm is correct and of predicted quality. 9/15/201543SCG(HSR)

44. Neg. HSR Use Case (continued) Exit condition: winner and loser are determined. Quality requirements: programming language, computational model: decision tree 9/15/201544SCG(HSR)

45. 1 0 1 3 2 x yz yes no u highest safe rung HSR(x,1)<=x-1 45 2 x-1 x-2 depth is x-1 9/15/2015SCG(HSR)

46. Bob has the following claims HSR(4,1)<=4 HSR(9,2)<=4 HSR(9,2)<=3 HSR(8,3)<=3 HSR(4,2)<=2 HSR(11,2)<=4 HSR(12,2)<=4 Alice makes a decision for each claim: defendable/refutable (refute function) defendable: Alice provides decision tree and Bob cannot find a bug. refutable: Bob provides decision tree and Alice finds a bug. To make the game more interesting: defendable claims are treated first 9/15/201546SCG(HSR) If defendable, can it be strengthened?

47. Play Game in class (abbreviated rules) Role Alice (1-3 students from class) Role Bob (the rest of class) Role Nina (3 students from class) Alice chooses two claims: HSR(9,2)<=3, HSR(11,2)<=4 that she thinks she can refute. Now play! Intro SCG47

48. Who is the winner? Nina keeps score. Initially Alice and Bob have 10 points. Intro SCG48

49. Bob has the following claims HSR(4,1)<=4 HSR(9,2)<=4 HSR(9,2)<=3 HSR(8,3)<=3 HSR(4,2)<=2 HSR(11,2)<=4 HSR(12,2)<=4 Alice makes a decision for each claim: defendable/refutable (refute function) defendable: Alice provides decision tree and Bob cannot find a bug. refutable: Bob provides decision tree and Alice finds a bug. To make the game more interesting: defendable claims are treated first 9/15/201549SCG(HSR)

50. Focus on HSR(11,2)<=4 – Alice provides decision tree. HSR(12,2)<=4 9/15/201550SCG(HSR)

51. 3 1 0 6 12 4 3 5 9 9 7 6 87 2 4 5 8 x yz yes no u highest safe rung Highest Safe Rung Decision Tree HSR(9,2)=5 51SCG(HSR)9/15/2015 Bob, Nina check: refutation by Bob successful. Alice loses. Alice: 2 points, Bob 10 points How could Alice have won?

52. Magic for now 0 1 2 3 4 5 6 7 8 9 10 3 2 1 4 7 5 6 HSR(11,2)<=4 9 8 10

53. Principle of Algorithm Design Instead of focusing on what changes from level to level, focus on what stays the same. Find the invariant.

54. Initial Project Description http://www.ccs.neu.edu/home/lieber/courses /se-courses/cs5500/sp11/projects/problem- statement.html http://www.ccs.neu.edu/home/lieber/courses /se-courses/cs5500/sp11/projects/problem- statement.html 9/15/2015SCG(HSR)54

55. Outline Introduction – Popper Science, Renaissance History: Tartaglia and Fior Definition of SCG – Example (Highest safe rung) Applications: Teaching, Software Development, Research Claims with secrets and other protocol variants Output of SCG, Equilibrium Advantages and Disadvantages Conclusions Intro SCG55

56. Applications: Software Development Software Development Teaching Constructive Domains Intro SCG56

57. Gamification of Software Development etc. Want reliable software to solve a computational problem? Design a game where the winning team will create the software you want. Want to teach a STEM domain? Design a game where the winning students demonstrate superior domain knowledge. Intro SCG Doesn’t TopCoder already do this? STEM = Science, Technology, Engineering, and Mathematics 57

58. SCG and TopCoder SCG is an abstraction and generalization of what TopCoder does. Intro SCG58

59. 59 10/16/09Can DM and ML help? Software Development Skills Needed when avatar caregiver is human. Knowledge about domain X needs to be developed by students or taught to them and understood and put into algorithms (propose- oppose-provide-solve) that go into the avatar. This tests both whether the knowledge about X is understood as well as the programming skills of caregiver. Intro SCG

60. The Traditional Approach Solver A Static Benchmark Solver B Solver C Team A Team B Team C Parameterized by the domain. Software: Solving HSR Problem: construct decision tree of min. depth measure how close to minimum HSR(9,2)=4 HSR(25,2)=7 Ranking 60Intro SCG

61. The Bio-Inspired Approach Team A Solver A prop-opp A Team C Solver C prop-opp C Team B Solver B prop-opp B Virtual World (Game) Ranking Parameterized by the domain. Avatar A Avatar C Avatar B Dynamic Benchmark 61Intro SCG

62. A Virtual World Avatar’s View Administrator Avatar Opponents’ communication, Feedback Claims, Problems, Solutions Results Problems: Benchmark output Solutions: Software output Claims: statements about algorithms 62Intro SCG

63. What Scholars think about! If I propose claim C, what is the probability that – C is successfully refuted – C is successfully strengthened If I try to refute claim C, what is the probability that I will fail. If I try to strengthen claim C, what is the probability that I will fail? 63Intro SCG

64. SCG = Scientific Community Game Make software development more scientific. Software developers build reputation – propose and defend claims about their software – oppose claims made by others refute claims strengthen claims claim includes refutation protocol Intro SCG64

65. Who are Alice and Bob? They are avatars developed by real Alice and real Bob. Alice and Bob compete with 10 other avatars in a full-round robin tournament. Who is the winner: The avatar with the highest reputation, i.e., the avatar who has the strongest, not successfully opposed claims (like in a real scientific community). Intro SCG65 Why a web application with avatars? Fair Evaluation.

66. What is SCG(X) Intro SCG66 no automation human plays full automation avatar plays degree of automation used by scholar our focus some automation human plays 0 1 more applications: test constructive knowledge transfer to reliable, efficient software avatar Bob Alice

67. Real Scholars and Avatars: Same rules Are encouraged to 1.propose claims that are not easily strengthened. 2.offer claims that they can successfully support. 3.strengthen others’ claims, if possible. 4.stay active and propose new strong claims or oppose others’ claims. 5.become famous! 67Intro SCG

68. What we want Engage software developers – let them produce software that models an organism that fends for itself in a real virtual world while producing the software we want. Have fun. Focus them. – let them propose claims about the software they produce. Reward them when they defend their claims successfully or oppose the claims of others successfully. Intro SCG68 Clear FeedbackSense of Progress Possibility of Success Authenticity (Facebook)

69. SCG Gamification of software development for computational problems A Sociotechnical System for knowledge dissemination, innovation, and integration 69Intro SCG

70. Life with SCG(X) with SCG structured collaboration between software developers, frequent feedback propose and oppose non- trivial claims to gain reputation. Drive to win knowledge accumulation in claims that have not been opposed successfully management effort goes into X without SCG collaboration is unstructured, less effective reputation gain is delayed knowledge is scattered in emails, programs and minds more management effort required 70Intro SCG

71. Software Engineering Properties fostered by SCG Reliable (otherwise the avatar is removed from the game) Flexible, modular (otherwise the avatar cannot be easily updated between tournaments) Efficient (otherwise you cannot defend your claims and oppose the claims of others) Intro SCG71 Adaptive and Aspect-Oriented Software is relevant!

72. State of SCG-Avatar: Our Vision Companies come to SCG website and define a competition by defining a claim domain X. Participating teams get baby avatars generated from X that participate in daily competitions. Competition generates a wealth of information: educated employees, good (undefeated) software, good algorithms, good potential employees. Reward is paid to the winner. Intro SCG72

73. State of SCG-Avatar: Our Vision Not only companies but faculty members who want to give their students a rich learning experience for computational problem X. Or editors of special issues in journals who want to use a competition to get a real world comparison of all approaches to solve computational problem X. Intro SCG73

74. Avatars propose and oppose Intro SCG74 CA1 CA2 CA3 CA4 egoistic Alice egoistic Bob reputation 1000 reputation 10 CB1 CB2 opposes (1) provides problem (2) solves problem not as well as she expected based on CA2 (3) WINS! LOSES proposed claims transfer 200 social welfare Life of an avatar: (propose+ oppose+ provide* solve*)*

75. What is SCG(X)? Teams Design Problem Solver Develop Software Deliver Avatar Avatar AliceAvatar Bob Administrator SCG police I am the bestNo!! Let’s play constructively 75Intro SCG Team Alice Team Bob

76. competitive / collaborative Intro SCG76 Avatar Alice: claim C Avatar Bob: opposes C, refutes: provides evidence for !C loses reputation rwins knowledge k wins reputation rmakes public knowledge k

77. Outline Introduction – Popper Science, Renaissance History: Tartaglia and Fior Definition of SCG – Example (Highest safe rung) Applications: Teaching, Software Development, Research Claims with secrets and other protocol variants Output of SCG, Equilibrium Advantages and Disadvantages Conclusions Intro SCG77

78. Protocol Variants secrets: approximation problems involving trusted third party – renaissance: exchange of problems Intro SCG78

79. Example: Triple HSR Alice claims ({(25,2,0), (25,2,1), (25,2,2), (25,2,3), …,(25,2,25)},9/25, 5 seconds) Refutation Protocol: – Bob refutes (25,2,17) – Alice solves problems (25,2,*) by providing decision tree to trusted third party which reveals path p from root to 17. – predicate: p is valid and length(p) <= 9 79Intro SCG Highest Safe Rung

80. Protocol Variation Secrets problem has public and private part, private part is a secret solution predicate has secret as argument 80Intro SCG

81. Protocol Variation Secret Program for SCG-Avatar problem has public and private part, private part is a secret solution and goes to administrator Alice gives her algorithm to administrator who applies it to public part of problem predicate has secret as argument 81Intro SCG

82. Example Claims involving secrets My algorithm can solve more problems using resources r than your algorithm using r. If I create problems for you for which I have a solution, you cannot recreate or approximate the solution with quality q using resources r. 82Intro SCG

83. Output and Equilibrium Rich tournament history What is an equilibrium in SCG? Intro SCG83

84. Soundness Theorem SCG is sound: The avatar with the best algorithms / knowledge wins (there is no way to cheat) – best: within the group of participating avatars – issues: Does an avatar win because she is good at solving? Or good at proposing, opposing and providing? Answer: proposing, opposing and providing all reduce to solving. Intro SCG84

85. SCG Equilibrium reputations of scholars are stable the ranking of the scholars is invariant from tournament to tournament the science does not progress; bugs are not fixed, no new ideas are introduced extreme example: All scholars are perfect: they propose optimal claims C(ps,q) that can neither be strengthened nor refuted. Intro SCG85

86. [Scientific Innovation in X] Avatars get skills programmed into them by clever scientists in domain X. Scientists use data mining to learn from competitions and manually improve the avatars. [Machine Learning Innovation in X] Avatars get skills programmed into them by an avatar caregiver programmed with learning skills and data mining skills for domain X. Avatar gets updated automatically. Survival in SCG(X) 86Intro SCG second-order environment!

87. Blame assignment Where is the proposer to blame? – Bad claim that is refuted. – Bug in problem finding algorithm? – Bug in problem solving algorithm? 87Intro SCG

88. How to use SCG(X) Company AB needs new ideas about how to solve optimization problems in domain X. Define claims language for X – X-problems – claims, includes protocol Submit claims language definition to SCG server. 88Intro SCG

89. How to use SCG(X) Offer prize money for winner with conditions, e.g., performance must be at least 10% higher as performance of avatar XY that AB provides. 10 teams from 6 countries sign up, committing to 6 competitions. Player executables become known to other players after each competition. One team from company AB. The SCG server sends them the basic avatar and the administrator for testing. 89Intro SCG

90. How to use SCG(X) Game histories known to all. Data mining! First competition is at 23.59 on day 1. Registration starts at 18.00 on same day. The competition lasts 2.5 hours. Repeat on days 7, 14, … 42. The final winner is: Team Mumbai, winning 10000 Euro. Delivers source code and design document describing winning algorithm to AB. 90Intro SCG

91. Benefits for company AB of using SCG(X) Teams perform know-how retrieval and integration and maybe some research. – Participating teams try to find the best knowledge in the area. – Claims language gives control! The non-refuted claims give hints about new X- specific knowledge. A well-tested solver for X-problems that integrates the current algorithmic knowledge in field X. 91Intro SCG

92. Outline Introduction – Popper Science, Renaissance History: Tartaglia and Fior Definition of SCG – Example (Highest safe rung) Applications: Teaching, Software Development, Research Claims with secrets and other protocol variants Output of SCG, Equilibrium Advantages and Disadvantages Conclusions Intro SCG92

93. Benefits/Disadvantages Benefits – competitive / collaborative – structured feedback, game history – Teaching – Research – Software Development Dynamic testing and evaluation Disadvantages – addictive Intro SCG93

94. Disadvantages of SCG The game is addictive. After Bob having spent 4 hours to fix his avatar and still losing against Alice, Bob really wants to know why! Overhead to learn to define and participate in competitions. The administrator for SCG(X) must perfectly supervise the game. Includes checking the legality of X-problems. – if admin does not, cheap play is possible – watching over the admin 94Intro SCG

95. How to compensate for those disadvantages Warn the scholars. Use a gentleman’s security policy: report administrator problems, don’t exploit them to win. Occasionally have a non-counting “attack the administrator” competitions to find vulnerabilities in administrator. – both generic as well as X-specific vulnerabilities. 95Intro SCG

96. Benefits of SCG Social Welfare – Supported knowledge Claims are refuted and strengthened. Better supported knowledge comes from better algorithms and software. 96Intro SCG

97. Advantage: Democratic Problem to be solved: Develop the best practical algorithms for solving computational problems in domain X. Issue: There are probably hundreds of papers on the topic with isolated implementations. What are the best practical algorithms? Our solution: Use the scientific community game SCG(X) with a suitably designed claims language to compare the software. The winning avatar has the best practical algorithms/software. 97Intro SCG

98. Experience with MAX-CSP MAX-CSP Problem Decompositions T-Ball (one relation), Softball (several relations, one implication tree), Baseball (several relations). ALL, SECRET 98Intro SCG

99. Stages for SECRET T-Ball MAXCUT – R(x,y)= x!=y – fair coin ½ – maximally biased coin ½ – semi-definite programming / eigenvalue minimization 0.878 99Intro SCG

100. Stages for SECRET T-Ball One-in-three – R(x,y,z) = (x+y+z=1) – fair coin: 0.375 – optimally biased coin: 0.444 100Intro SCG

101. Stages for ALL Baseball Propose/Oppose/Provide/Solve – based on fair coin – optimally biased coin correctly optimize polynomials – correctly eliminate noise relations – correctly implement weights – … 101Intro SCG

102. References Karl Popper, Conjectures and Refutations, London: Routledge (1963). Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. The Journal of the Learning Sciences, 3(3), 265-283. Renaissance: Tartaglia and Fior challenge (1535). Intro SCG102

103. Conclusions To address a problem domain X: – “map it to second life”: define a scientific community game for X on the web: SCG(X) – let the game SCG(X) run a few times and choose the winner Benefits – Evaluates fairly, frequently, constructively and dynamically. Encourages retrieval of state-of-the-art know-how, integration and discovery. – Challenges humans, drives innovation, both competitive and collaborative. – Avatars point humans to what needs attention in problem solution / software. Intro SCG103

104. Conclusions Broad applicability, e.g., SCG(X) provides a software process for developing software for computational problems. Benefits – Social Engineering: makes it fun through game. – Fair: Only hard work makes you win. – Engage a large community on one domain X. Intro SCG104

105. end Intro SCG105

106. State of Avatar SCG Domain is hard-wired to Constraint Satisfaction Problems One Master student worked on making it generic but work is not complete. Intro SCG106