1. Team Formation between Heterogeneous Actors Arlette van Wissen Virginia Dignum Kobi Gal Bart Kamphorst

2. Introduction How to make decisions in a fast-paced and dynamic domain in which humans and agents interact? The Problem 2

3. Introduction How to make decisions in a fast-paced and dynamic domain in which humans and agents interact? The Problem 3

4. Introduction Team Formation N - T T N 4

5. Introduction To become part of successful teams, one has to deal with the following problems: team formation how to identify the members of a successful team how to reach an agreement on the allocation of the payoffs team maintenance (intention reconciliation) manage conflicts among made commitments Team Formation 5

6. Introduction How to make decisions in a fast-paced and dynamic domain in which humans and agents interact? Humans are not completely rational actors. (Kagel & Roth, 1995) Social factors influence human behavior. (Loewenstein, 1989, Camerer, 2003) The Problem 6 Fairness

7. Introduction How to make decisions in a fast-paced and dynamic domain in which humans and agents interact? - changing environment - no predefined teams - non-binding agreements Trust The Problem 7

8. Introduction How to make decisions in a fast-paced and dynamic domain in which humans and agents interact? Social factors influence cooperation between humans and agents. (van Wissen et al., 2009) The Problem 8 Actor Type People behave differently towards agents and other people. (Blount 1995, Sanfey 2003 )

9. Related Work Team Formation Existing work on team formation: Pays less attention to human-agent interaction. Uses models that generally do not consider trust or nature. Focuses on formal analysis. Uses simplifying assumptions. 9

10. Experimental Design Package Delivery Domain Fast paced domain with uncertainty and commitment. Team Formation: initiators and members. Social dilemmas: 1. working together? 2. allocation of payoff? 3. staying together? 10

11. Experimental Design Package Delivery Domain 11

12. Experimental Design Package Delivery Problem in Colored Trails 12

13. Experimental Design Fairness, Trust Empirical Methodology ability to choose team members & transferable payoff Actor Type repeated interaction, defection deception 13

14. Experimental Design Package Delivery Problem in CT - 6 players per game ( P ) - 3 colors (P/2) 14

15. Experimental Design Package Delivery Problem in CT - 6 players per game ( P ) - 3 colors (P/2) 15

16. Experimental Design Package Delivery Problem in CT - 6 players per game ( P ) - 3 colors (P/2) - 6 large packages( P ) - 12 small packages(2 P ) 16

17. Experimental Design Package Delivery Problem in CT team formation game with: - payoff small package = 3 payoff large package with 2 players = 60 payoff large package with 3 player = 180 - imperfect information : players do not have knowledge of all actions and behavior of the players in the game and have partial visibility 17

18. 18

19. Experimental Design movie 19

20. The Experiment 2 experiments, 18 subjects 44% male, 56% female 72% students 5 rounds of 5 – 14 min payment corresponding to performance 20

21. Results & Discussion Team Formation Result 1 These factors are shown to significantly affect performance: joining teams (pearson correlation, r = 0.56) initiating teams (pearson correlation, r = 0.42) delivering packages individually (pearson correlation, r = 0.31) 21

22. Results & Discussion Team Formation Result 2 Subjects showed a preference to interact with those they successfully interacted with before. 22 trust value number of times subjects cooperated in the past in any team configuration likelihood of future interaction

23. Results & Discussion Team Formation successful teamsfrequency 01 02 04 05 12 1 13 15 23 24 2 34 1 35 45 012 015 024 045 12312 135 2342 3451 23

24. Results & Discussion Team Formation 24

25. Results & Discussion Intention Reconciliation 25 Result 3 Trust is more important to the decision of defection than the height of outside offers. > No significant increase of payoff for accepted outside offers. >Small but significant correlation between accepted outside offers and trust value of initiator (0.29).

26. Results & Discussion Participant Type Result 4 Players offer humans significantly more fair splits than they offer agents. (combined t-test, p < 0.0001) to people: 94% fair to agents: 82% fair 100 % fair50 % fair 2-player team 3015 3-player team 6030 Result 5 The nature of participants does not significantly affect: 1.the choice of team partners 2.the acceptance of offers 3.defection behavior 26

27. Results & Discussion Participant Type 27

28. Conclusions People are just as loyal and trusting towards agents as to humans. agent-initiated teamwork and working alongside autonomous systems (search-and-rescue, personal assistants, decision support) People but offer agents less, thereby valuing them differently from humans. agents need to behave and appear natural and ‘human-like’ (e-commerce, bidding, games, personal assistant) 28

29. Conclusions People prefer to work with players they have successfully worked with before. refer to previous interactions, have memory (games, companions) 29

30. Future Work 1.Computational Model 2.Belief Desire Intention (BDI) Agents 3.Pre-established payoff distributions 30

31. Thank you. 31

32. 32

33. Game Flow Initiator 33

34. Game Flow Initiator 34

35. Game Flow Member 35

36. Game Flow Member 36

37. Related Work Trust For an actor a to be said to trust another actor b with respect to a particular goal g, a must have the following beliefs (castelfranchi, 1998, 2001) : Competence Belief: b is useful for achieving g and is able to provide the expected result Disposition Belief: b is not only capable, but also willing to do what is necessary to achieve g Dependence Belief: the results and rewards of achieving g depend on the involvement of b Fulfillment Belief: g will come about due to b ’s involvement 37

38. Results & Discussion Nature Result 7 The nature of participants does not significantly affect the choice of team partners or the acceptance of offers. 38

39. Introduction Types of interactions: - cooperative and helpful interactions - competitive interactions - cooperative interactions in competitive scenarios non-cooperative games - self-interested actors who can make non-binding commitments - basic modeling unit is the individual cooperative games - players can make binding commitments - communication and negotiation between the players is allowed - groups of players (teams) may enforce cooperative behavior - basic modeling unit is the group team Formation 39

40. Conceptual Design Assumptions in CF Interchangeability Prev work All potential members bring the same utility to a team. Our work Some potential members are preferred over others. Membership Prev work Membership to a team is equally available to everyone. Our work Members have to meet certain requirements for membership to be available to them. Conflict Prev work Conflict is eliminated by making agreements binding. Our work No conflict-free environment since agreements are not binding. 40

41. 41

42. 42

43. 43

44. 44

45. 45

46. 46

47. Introduction How to make decisions in a fast-paced and dynamic domain in which humans and agents interact? The Problem 47

48. What strategy did you use for choosing your team members? ``Whether members were reliable. I could give computers a smaller share without feeling guilty. I did build a good history with one other human player.’’ ``I chose the computers mostly, since I thought that they would demand less points.’’ Results & Discussion Nature 48

49. Conceptual Design Identify the extent to which these factors affect behavior in heterogeneous systems. Derive principles that designers of such systems could use to construct agents that are able to participate effectively in teams. How do nature and trust influence people’s decisions in mixed team formations? Objective 49

50. Outline 1.Introduction 2.Related Work 3.Conceptual Design 4.Experimental Design 5.The Experiment 6.Results & Discussion 7.Conclusions 8.Future Work 9.Contributions 50

51. Results & Discussion 1.Survey -preferences -strategies 2.Log -proposals -teams -defections 51

52. Experimental Design team formation consists of two steps: 1.The initiator invites members who thereafter join the team. 2.The team delivers the package. attempted team Package Delivery Domain 52 i ?

53. Experimental Design team formation consists of two steps: 1.The initiator invites members who thereafter join the team. 2.The team delivers the package. formed team Package Delivery Domain 53 i

54. Results & Discussion Team formation consists of two steps: 1.The initiator invites members who thereafter join the coalition. 2.The coalition delivers the package. formed team A team is formed when the initiator has invited the required members for a team and the members have agreed to be part of that team. Package Delivery Domain 54

55. Results & Discussion Team formation consists of two steps: 1.The initiator invites members who thereafter join the coalition. 2.The coalition delivers the package. successful team A successful team is a formed team that succeeded to deliver a large package to the goal. Package Delivery Domain 55

56. Results & Discussion Team formation consists of two steps: 1.The initiator invites members who thereafter join the team. 2.The team delivers the package. failed team An unsuccessful team is a team that was dissolved (by defection) before it was able to deliver the package. Package Delivery Domain 56

57. Results & Discussion Intention Reconciliation Result 5 Players with a high defection rate are as successful as those with a low defection rate. 57

58. Results & Discussion team Formation Result 2 Players created more 3-player teams than 2-player teams. (goodness of fit, p < 0.00001) Result 3 No difference in defection rates in 2- and 3-player teams. 58