Team Formation between Heterogeneous Actors

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

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

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

4. Introduction Team Formation N N - T T

5. Introduction Team Formation To become part of successful teams, one has to deal with the following social dilemmas: team formation working together? allocation of payoff? team maintenance (intention reconciliation) staying together? - Identify the tradeoffs between fairness, trust and participant type in dynamic team interactions. - Derive principles that can be used to construct agents that are able to participate effectively in these settings.

6. Introduction The Problem 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) Fairness

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

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

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

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?

11. Experimental Design Package Delivery Domain

12. Experimental Design Package Delivery Problem in Colored Trails

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

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

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

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

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

19. Experimental Design movie

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

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)

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

23. Results & Discussion Team Formation

24. Results & Discussion Intention Reconciliation 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).

25. 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: avg. 94% fair to agents: avg. 82% fair • Result 5 • The nature of participants does not significantly affect: • the choice of team partners • the acceptance of offers • defection behavior

26. Results & Discussion Participant Type

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

29. Future Work • Computational Model • Belief Desire Intention (BDI) Agents • Pre-established payoff distributions

30. Thank you.

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32. Game Flow Initiator

33. Game Flow Initiator

34. Game Flow Member

35. Game Flow Member

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

38. Introduction team Formation 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

39. Conceptual Design

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

47. Results & Discussion Nature 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.’’

48. Conceptual Design Objective How do nature and trust influence people’s decisions in mixed team formations? • 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.

49. Outline • Introduction • Related Work • Conceptual Design • Experimental Design • The Experiment • Results & Discussion • Conclusions • Future Work • Contributions

50. Results & Discussion • Survey • preferences • strategies • Log • proposals • teams • defections