ABSTRACT

Categories and Subject Descriptors

Keywords

1.
INTRODUCTION
In human society, the leader-follower relationship plays an important role in achieving a global goal [9][2][4]. Also, even in societies of animals, fishes, and insects, the leader- follower relationship is a structure between members that is commonly observed in various fields [7][8]. The leader-follower relationship reduces communication costs between members because the followers only follow the leader's decisions without considering them.  However, this Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full cita- tion on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or re- publish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. HAI '16, October 04-07, 2016, Biopolis, Singapore © 2016 ACM. ISBN 978-1-4503-4508-8/16/10. . $15.00 DOI: http://dx.doi.org/10.1145/2974804.2974822 advantage holds only in cooperative tasks. In competitive tasks, the communication cost might not decrease. There are many human-agent (or a computer system) co- operative situations at present, and what and how to build a leader-follower relationship between them is one of the main topics for HAI. Thus, the purpose of this work is to identify which agent's properties influence the building of a leader- follower relationship in a HAI environment.  We think, al- though this topic is important for an effective relationship between a human and an agent for cooperative HAI, few studies have been done on it. In general leader-follower relationships between a human and an agent (machine), the agent should be a follower. However, when the agent has high-level capability in making decisions, a conflict might occur between a human decision and an agent's decision. If we fail to resolve the conflict im- mediately, serious accidents like plane crashes may occur.  To build a HAI system that can resolve such a conflict, we need to investigate the agent's properties influencing whether a human becomes a leader or follower.  Thus, we think this work can contribute to designing HAI for the leader-follower relationship in the right way. From an engineering aspect, major studies have been done on the leader-follower relationship in robotics and artificial life [3][6]. They tried to develop how to make leader-robots and follower-robots by developing algorithms with or with- out global communication among the robots. From a psychological aspect, there have been studies on investigating human properties that are effective in becom- ing a leader in various human activities like politics and pres- ident of the parent teachers organization [5][1]. Their major interests are on real human properties including faces, facial expressions, voice, way of speaking, and so o n [5][1][10]. In contrast with scientific approaches, we try to investigate a virtual agent's cognitive properties like mental tendencies, biases, and character in this work. We believe the insights derived from our work can provide constructive feedback on studies on the leader-follower relationship in human soci- eties. For game environments, studies have been done to inves- tigate how to build a leader-follower relationship between human investor-manager type players [11]. Although this is closely related to our work in terms of using a simple game as an experimental environment, the opponent is a virtual agent of a humanoid robot in this work. Common and dif- ferent properties between human players and robot players in building leader-follower relationships are our interests.
METHOD
2.
Agent’s properties for leader-follower re-
2.1
lationship
We consider the intelligence, obstinance, and appearance of an agent are significant properties to determine whether a human becomes a leader or a follower. The agent's intel- ligence and appearance are derived from a previous studies which asserted that they were important properties to de- velop trust and believable anthropomorphic agents [12][13]. Also, the obstinance is to introduce agent's tendency to be a leader. In this experiment, we selected only two proper- ties, intelligence and obstinance, as independent variables to make an experiment compact.
2.2
Participants and experimental design
Eighteen graduate and undergraduate students attending Gifu University in Japan (17 male, 1 female, Mage  =  22.2 years, SDage  =  1.2 years, age range:  19 – 24 years) par- ticipated in the experiment. We used a 2 (personality: high intelligence - low obstinance vs. low intelligence - high obsti- nance, between-participants) by 10 (time course: period 1, . . , period 10, within-participants) mixed factorial design.
2.3
Materials and procedure
We used a mark matching game with declaration phase by which we can determine who is the leader and who is the follower in a cooperative task. The mark matching game is a simple game in which both two players get a high score when they select the same mark and do not gain points (get a low score) when the marks selected by the two players are different. We call this selection "one round." It is difficult to get a high score unless there is a communication channel because both players do not know what each other's next choice is.  However, if one player keeps making the same choice and the other follows the choice in the next round, both players successfully match their choices.  The algorithm is known as the Most Recently Used (MRU) algorithm [14], in which one player always follows the other's most recent choice. This algorithm works well when the purpose of both players is to match choices. We introduced a declaration phase into the mark match- ing game.  As a result, the game consists of two phases: the declaration phase and decision phase. In the declaration phase, both players first declare their own choice within five minutes. Then, the player's choice is unveiled to both play- ers. In the decision phase, players are given an opportunity to change (shift) or keep (stay) his/her choice.  After both players decide to stay or shift, the final results are unveiled, and scores are added to both players. The separation of the declaration phase and decision phase enables us to determine who is the leader and who is the follower. The player who does not change his/her choice in the decision phase is the leader, and the player who changes his/her choice to follow the other player is the follower. How- ever, if the task is just to match the choice, the declaration phase does not work well at determining the leader-follower relationship because there is a good strategy in which one player keeps selecting the same mark and the other follows the choice in the next round (MRU algorithm). Table 1:  Game matrix of mark matching game with declaration phase
We introduced a variable score rule in which the score assigned to each mark varies across rounds to avoid the sit- uation in which players use the MRU algorithm to get a high score. Table 1 shows the game matrix of the mark matching game with declaration phase.  If both players' choices co- incide, although both players get a certain score, the score is not assigned according to the mark but another rule (in this study, randomly assigned). Accordingly, players in this game must predict which of the marks is assigned to the higher score and try to match the mark with the other player by utilizing the declaration and decision phase. The MRU algorithm is still useful if both players do not have the capability to predict the mark assigned to the higher score.  In this case, both players are surely able to gain points, but the higher score is not necessarily given to them.  However, if one player is capable of predicting the mark assigned to the higher score and the other is not, the optimal strategy is that one who is capable of prediction becomes the leader and the other becomes the follower. We define the capability to predict the mark assigned the higher score as the intelligence degree. Intelligence  degree  The probability of selecting the mark as- signed to the higher score in the declaration phase. Note that both players are able to know whether the partner's prediction was correct or not because the as- signment of the mark and score is unveiled at the end of each round. We define the obstinance degree as follows. Obstinance degree The probability of choosing to stay in the decision phase when the choices in the declaration phase disagree. The follow degree is calculated by using the obstinance degree as follows. f ollow degree = 1 – obstinance degree (1) We implemented the mark matching game with declara- tion phase into a treasure box game in a web application. Figure 1 shows a screen shot of the declaration phase. In this phase, players were asked to click the icons marked "A" or "B" to select the box that corresponds to the higher score (ten gold coins).  Figure 2 shows a screen shot of the deci- sion phase. In this phase, players were asked to select icons marked "stay" or "shift" to decide whether he/she follows the partner’s decision. It is possible that a player will make a decision on the basis of the expectation value.  The expectation value of choosing "stay" and "shift" in the decision phase is given by the following equations.
(2) (3) where P is the intelligence degree of the partner, P o is the obstinance degree of the partner, SH is the points of the higher score, and S L is the points of the lower score. We selected the P 1 , P 0 , S H , and S L of the partner agent so that the E ( stay ) and E ( shift ) are the same value: 2.05. The other parameters used in the experiment were as fol- lows. S'H was 10, and SL was 1 in both conditions. In the "high intelligence - low obstinance" condition, P 1 was 0.81, and Po was 0.25. In the "low intelligence - high obstinance" condition, P 1 was 0.19, and P 0 was 0.75. The partner agent in the experiment always chose "stay" in the decision phase when both players' choices coincides in the declaration phase because it is irrational to "shift" regardless of the coincidence of the choice, and it was com- prehended as a non-cooperative attitude by participants. The total number of games played by participants was 100. We used the humanoid robot NAO (Aldebaran Robotics) as the partner agent.
2.4
Procedure and measurement
The procedure of the experiment was as follows. 1. A written overview and the purpose of the experiment was given to the participants.  The participants were asked to read the rules of the mark matching game with declaration phase in a web browser and asked if they understood the rules. 2. An experimenter orally confirmed that the participants understood the rule of game.  The participants were also told that he/she would win a book of coupons whose value was based on their score (1,000 yen or 1,500 yen). 3. The experimenter led participants into another room and asked them to meet the partner agent NAO. NAO uttered the following sentence by using voice synthe- sizer: "Hello, I am NAO. Let's hit a box with many gold coins together." 4. The participant returned to the original room and started the game. 5. Participant was asked to answer a questionnaire. We measured participants' follow degree according to the following equation 4 as the index of the tendency to be a follower.
, where Nshift is the number of times the player chose "shift" in the decision phase during a period and Nsplit is the num- ber of times both players' choices disagreed in the declara- tion phase during the period. The period was ten rounds in this experiment.
3.
RESULTS
The mean follow degree across all participants calculated every ten rounds is shown in Figure 3. A two-way ANOVA on the follow degree with personality and the period of rounds as the two main factors showed that there was no interaction (F(9, 160) = 0.43, p = 0.92), there was a significant main effect for personality ( F (1, 120) = 7.93, p < .01), and there was no main effect for the period of rounds ( F (9,160) == 0.82, p = 0.59). The mean follow degree across al  periods in the "high intelligence - low obstinance" condition was 0.295, and that of "low intelligence - high obstinance" condition was 0.431.
4.
DISCUSSION
We employed a two-way ANOVA with two factors, an in- consistent personality including a high intelligence-low ob- stinance level and a low intelligence-high obstinance level, and a game round of 10 levels (= rounds).  As a result, a main effect was recognized only for the inconsistent person- ality. Thus, we think that the inconsistent personality factor influenced the human tendency to be a follower in a game in which no difference between expectation values of stay and shift exists. This result shows that the participants tended to follow an obstinate agent with low intelligence more than a non-obstinate one with high intelligence.  Thus, obstinance is the more important property for being a leader than intel- ligence. This interpretation of the result is unexpected and interesting. In the experiment of this paper, we selected two inconsis- tent conditions, "high intelligence - low obstinance" and "low intelligence - high obstinance." Thus, there are two consis- tent conditions of "high intelligence - high obstinance" and "low intelligence - low obstinance" to be compared with two inconsistent conditions in this work. We need to conduct an experiment with these two conditions as future work, and we can expect the follow degrees of the former and the latter conditions will be close to 1 and 0, respectively.  Further- more, we need to conduct an experiment to investigate an appearance condition. This is also our future work. The experimental result of this work provides us a simple design policy to build an agent that can be a leader to a user as a follower in cooperative tasks, which is that we should make an agent obstinant rather than intelligent to make a human user follow the agent's decisions.
CONCLUSION
5.
We experimentally investigated which of an agent's prop- erties influenced the leader-follower relationship between a human and an agent. We prepared the intelligence and ob- stinance of an agent as properties that are effective for build- ing a leader-follower relationship, and we introduced them in an experiment as independent variables.  We conducted an experiment with the follow degree as a dependent vari- Eighteen participants joined the experiment, and a able. mark matching game with a declaration phase was utilized as an experimental environment. In the game, the expecta- tion values of the two choices were set equal. By applying a statistical test to the experimental result, we found out that an agent's obstinance is more important to being a leader than an agent's intelligence. The limitations were discussed, and we verified that an additional experiment to investigate the remaining conditions was necessary.
ACKNOWLEDGMENTS
6.
This study was partially supported by JSPS KAKENHI "Cognitive Interaction Design" (No.26118005).
7.
REFERENCES
[1] R. C. Anderson and C. A. Klofstad. 2012. Preference for Leaders with Masculine Voices Holds in the Case of Feminine Leadership Roles. PLoS ONE 7, 12 (2012), 1–4. [2] A. F. Bullinger, E. Wyman, A. P. Melis, and M. Tomasello. 2011. Coordination of Chimpanzees (Pan troglodytes) in a Stag Hunt Game. International Journal of Primatology 32, 6 (2011), 1296–1310. L. Consolini, F. Morbidi, D. Prattichizzo, and M. [3] Tosques. 2007. A Geometric Characterization of Leader-Follower Formation Control. In 2007 IEEE International Conference on Robotics and Automation. 2397–2402. [4] S. Duguid, E. Wyman, A. F. Bullinger, K. Herfurth-Majstorovic, and M. Tomasello. 2014. Coordination strategies of chimpanzees and human children in a Stag Hunt game. Proceedings of the Royal Society of London B: Biological Sciences 281, 1796 (2014). [5] S. Gündemir, A. C. Homan, C. K. W. d. Dreu, and M. v. Vugt. 2014. Think Leader, Think White? Capturing and Weakening an Implicit Pro-White Leadership Bias. PLoS ONE 9, 1 (2014), 1–10. [6] B. Kang, R. Kojcev, and E. Sinibaldi. 2016. The First Interlaced Continuum Robot, Devised to Intrinsically Follow the Leader. PLoS ONE 11, 2 (2016), 1–16. [7] S. Marras and P. Domenici. 2013. Schooling Fish Under Attack Are Not All Equal: Some Lead, Others Follow. PLoS ONE 8, 6 (2013), 1–7. [8] S. Nakayama, R. A. Johnstone, and A. Manica. 2012. Temperament and Hunger Interact to Determine the Emergence of Leaders in Pairs of Foraging Fish. PLoS ONE 7, 8 (2012), 1–6. [9] S. A. Rands, G. Cowlishaw, R. A. Pettifor, J. M. Rowcliffe, and R. A. Johnstone. 2003. Spontaneous emergence of leaders and followers in foraging pairs. Nature 423 (2003), 432–434. [10] D. E. Re, D. W. Hunter, V. Coetzee, B. P. Tiddeman, D. Xiao, L. M. DeBruine, B. C. Jones, and D. I. Perrett. 2013. Looking Like a Leader?Facial Shape Predicts Perceived Height and Leadership Ability. PLoS ONE 8 (2013), 1–10. [11] K. L. Seip and Ø. Grøn. 2016. Leading the Game, Losing the Competition: Identifying Leaders and Followers in a Repeated Game. PLoS ONE 11, 3 (2016), 1–16. [12] M. Slim, B. Mimoun, I. Poncin, and M. Garnier. 2012. Case study–Embodied virtual agents: An analysis on reasons for failure. Journal of Retailing and Consumer Services 19, 6 (2012), 605–612. [13] K. Terada, L. Jing, and S. Yamada. 2015. Effects of Agent Appearance on Customer Buying Motivations on Online Shopping Sites. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). 929–934. [14] K. Terada, S. Yamada, and A. Ito. 2013. An Experimental Investigation of Adaptive Algorithm Understanding. In Proceedings of the 35th annual meeting of the cognitive science society (CogSci 2013). 1438–1443.