Reactive Movements of Non-humanoid Robots Cause Intention Attribution in Humans

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1 Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems San Diego, CA, USA, Oct 29 - Nov 2, 2007 ThC7.6 Movements of Non-humanoid Robots Cause Intention Attribution in Humans Kazunori Terada, Takashi Shamoto, Haiying Mei, and Akira Ito Abstract An artifact s behavior must be easily construed and interpreted as meaningful signals in a social or working context. In order to design such an artifact s behavior, we could exploit human psychological functions - theory of mind (ToM) - the ability to interpret other people s behavior in terms of intentional causal mental states such as beliefs, desires and intentions. In order to apply theory of mind to human-robot interaction, the mechanism that trigger intention attribution must be revealed. The present study examined the effect of reactive movements performed by a non-humanoid robot, including different shaped artifact: chair and cube, on the intention attribution. The result indicated that whether or not humans could construe behaviors of an artifact in terms of its goal depends on how human could attribute intention to the artifact and that reactive movements would be a cue for such mental state attribution. I. INTRODUCTION Tools allow us to extend our ability and improve our lives. From the stone implements of the Stone Age to mobile phones, artificially created tools have been controlled and manipulated according to human decisions. Recent advances in computer technology, however, have changed the relationship between humans and tools, allowing the tools to act autonomously and giving them decision making abilities. Of all tools, the humanoid robot may seem the most versatile, adaptable, and intelligent, because its human-like appearance gives us the impression that it can perform a variety of things. Humanoid robots would be most suitable tools for laboring instead of human beings in our everyday work, since our living areas are designed for human embodiment. Humanoid robots are aimed at performing tasks requested by humans, acting as a task mediator. Suppose there is a situation in which a man wants to sit on a chair, and the chair is far from him. In order to sit on a chair he must look for a chair and go to the chair. If there is a humanoid robot, the man can ask the humanoid robot to bring a chair for him, and the humanoid robot will get the chair and bring it to him. However, there is an alternative solution to simplify our physical life style: using simple autonomous and intelligent artifacts. Instead of mediating tasks, intelligent artifacts directly execute our physical demands by themselves. In the non-humanoid paradigm, we could directly ask the chair to come to us. K. Terada, T. Shamoto, and A. Ito is with Faculty of Engineering, Information Science, Gifu University, 1-1 Yanagido, Gifu, , Japan. Terada: terada@info.gifu-u.ac.jp, Shamoto: shamo@elf.info.gifu-u.ac.jp, Ito: ai@gifu-u.ac.jp H. Mei is with IBIDEN CO.,LTD., 2-1 Kanda-cho, Ogaki, Gifu , Japan In this paper, we consider non-humanoid robots or intelligent artifacts. The artifact s behavior must be easily construed and interpreted as meaningful information in a social or working context. In order to design such an artifact s behavior, we could exploit human psychological functions - theory of mind (ToM) - the ability to interpret other people s behavior in terms of intentional causal mental states such as beliefs, desires and intentions [1][2]. Theory of mind is a specific cognitive strategy to interpret and reason about the behavior of animated entities. By contrast, for inanimate entities, we use another cognitive strategy, such as naïve physics, through which we try to explain or predict physical phenomena such as a flying object s trajectory. Invoking the theory of mind mechanism by producing appropriate robot behavior leads to successful and smooth communication between humans and robots. Although perception of intentionality seems to be associated with higher-level cognitive mechanisms, researchers suggest that it is an automatic and immediate process. While some researchers argue that the ability to attribute intention to others is learned through experience with human agents [3][4], others suggest that this ability is an innate and hardwired brain function [5][6][7]. Recent infant studies indicate that goal attribution (understanding of goal-directed action) is present very early in infancy [8][9][10][3], suggesting that the ability of intention attribution is associated with special brain functions. While some researchers focus on the cognitive process in human-robot interaction, there have as yet been relatively few attempts focusing on the theory of mind issue in robotic research. There have been attempts to understand the ToM mechanism by using humanoid robots [11][12]. Some robotic researchers are trying to utilize the theory of mind mechanism in human-robot interaction [13][14][15][16][17]. In order to apply theory of mind to human-robot interaction, the mechanism by which intention attribution is triggered must be revealed. A growing body of literature in the field of cognitive psychology, developmental psychology and cognitive neuro-science investigate cues for triggering intention attribution [18][19][20][21]. A large variety of stimuli which invoke intention attribution are reported in this literature, including rationality [9], goal or goal-directedness [22], self-propelled motion [23][24][25], equifinality [8], spatial contingencies [26]. It remains unclear, however, which of these cues are either necessary and/or sufficient. There are some psychological reports on the human tendency to attribute human characteristics to movement of simple geometrical shapes, which has the potential to be /07/$ IEEE. 3715

2 beneficial to human-robot interaction. A well-known classic study of intention attribution to abstract figures was performed by Heider and Simmel [25]. They showed adult human subjects a film in which simple geometric figures moved around in a human-like way, performing actions such as chasing or fighting. Almost all the subjects ascribed anthropomorphic interpretation to these motions in terms of desires, intentions and beliefs. This finding was replicated by subsequent researchers [27]. Premack [6] and Baron-cohen [23] suggests that the detection of self-propulsion directly triggers the categorization of the object as an intentional agent. Intentional agents are self-propelled objects whose actions are caused by intentional mental states, who pursue goals, and can react contingently to the behavior of the other objects from a distance. According to these proposals, the detection of movement cues indicating agency is a necessary precondition for intention attribution to be used to interpret the behavior of the object. Bassili [26] argued that impressions of interaction and intentionality depend on temporal and spatial contingencies, respectively. Dittrich [28] found that the more direct the motion, the more likely it was to be interpreted as intentional; intentional motion was much easier to detect when the target moved faster than others than when it moved more slowly; recognition of intentionality was impaired but not abolished if the goal toward which the target was moving was invisible; and participants did not report intentional movement when the target was distinguished by brightness rather than the manner in which it moved. Most researchers in the field of psychology have used an experimental paradigm in which participants observe the animated behavioral interactions of figures on a computer display. In order to design methodologies in the context of human-robot interaction, however, we must investigate the human ability of intention attribution in a direct interaction paradigm. There have as yet been relatively few attempts made using the direct interaction paradigm, focusing on the theory of mind issue in robotic research [13]. The present study examines the effect of reactive movements of non-humanoids on intention attribution. In our previous studies, we presented subjects moving chair s actions to stimulate direction of attention detector (DAD) [7]; a specialized brain function used to determine whether one is the subject of another s attention through the direction of their eye, head, body and locomotion [16]. The chair robot s direction of attention detector (DAD)-stimulating actions were defined as actions which keep directing a subject. The result indicated that the DAD-stimulating actions changed the subject s stance and enabled him/her to discern its intention. The DAD-stimulating action, however, is clearly intentional, in that it cause the subject to easily attribute intention to chair s actions. movement, on the other hand, implicitly confirms intentionality, showing that the robot is always observing human behavior. Detecting whether or not a human attributes intention to entities is difficult because such mental state attribution is a subjective cognitive process and hard to measure. Retrieval methods for subjective mental states, which rely on subjective self-reporting have been criticized for methodological limitations [29]. Observers report their subjective percepts in response to the animations, and it is possible that higherorder cognitive processing is engaged in order to produce these descriptions [27]. Neuroimaging techniques such as functional magnetic resonance imaging (fmri) and positron emission tomography (PET) seem to be useful for examining mental processes without relying on self-reporting. These methods, however, restrict the subject s natural physical interaction due to the spatial and physical constraints of apparatus used in fmri and PET. Furthermore, the area of the brain that activates intention attribution is unclear. Thus, so far, the measuring method for detecting subjective mental states about intention attribution has not been established. In our study, we employ a questionnaire method in which we ask the subject which of Dennett s three stances did they take toward artifacts for understanding their behavior. The philosopher Dennett [2] proposed human cognitive strategies in which humans construe the behavior of other animate objects, including other humans, artifacts, and physical phenomena: intentional, design and physical stances. A physical stance, based on the laws of nature, is what we use to predict the action of a physical object, like a stone rolling down a slope. However, it is very tedious to apply a physical stance to a complex artificial system like an alarm clock. We expect an alarm clock to make a loud noise at a preset time when the time is set properly. We are predicting the action of an alarm clock according to the intention of its designer; this is a design stance. An intentional stance is employed when we predict the action of an object as if it has beliefs and acts according to its desire. The goal of the studies presented below is to investigate following three topics: 1) whether or not the reactive movements of a non-humanoid robot triggers intention attribution in humans, 2) how a human s stance (i.e. physical, design or intentional) affects his/her actions, and 3) whether or not differences in appearance of an artifact influence intention attribution and goal attribution. We conducted two experiments using differently shaped artifacts: a functionally shaped moving artifact (chair) and an abstract-shaped moving artifact (cube), in order to test the effects of the differences in appearance on intention attribution. A. Method II. EXPERIMENT I 1) Subjects: Sixteen university students and members of staff participated in the experiment. Subject ages ranged from 20 to 27 years. None had had prior knowledge about the experiment or experience in interacting with the artifact used in the experiment. 2) Apparatus and stimuli: A computer controlled chair performing a series of actions of was shown to the participant in the experimental room (see Figure 1). The experimental room was partitioned and the experiment was performed in 3716

3 TABLE II ACTION UNITS FOR SUBJECT S BEHAVIOR ANALYSIS. Category No. Subject s action Observing 1 Stay looking at the artifact 2 Move to keep a constant distance from the artifact 3 Look over the mechanism of the artifact 4 Move toward the artifact Interrupted 5 Subject s action was interrupted and stopped by the artifact s action 6 Subject stopped after the artifact stopped Probing 7 Wave limbs (hand or foot) 8 Take a large step towards the artifact 9 Jump in front of the artifact 10 Walk quickly in front of the artifact 11 Stop suddenly after moving in front of the artifact Fig. 1. Experimental environment and settings. TABLE I ACTION UNITS. Action vr (cm/sec) vl (cm/sec) duration (sec) forward or 2 backward or 2 turn right or 2 turn left or 2 rotate right or 2 rotate left or 2 half of the room; the area used in the experiment was 6m 5.5m. There was nothing but the chair in the experimental area. The participant was allowed to move freely within the experimental area. Two powered wheels (driven by 24V DC motor: maxon A-max 32 series) were installed to the chair to control its two-dimensional motion. The motors were controlled by a maxon mip 20 motor driver which was connected to a small Linux PC mounted below the seat. Wireless LAN allowed the experimenter to remotely operate the chair; in our experiment, the experimenter sent only the start command. The action used for a particular experiment was randomly selected from a combination of the six action units and two durations listed in Table I (vr and vl indicate wheel velocities) but the performance of the action was limited to a 160cm 160cm area. The action sequence was identical throughout the experiment; that is, all of the subjects viewed the same action sequence. While the maximum duration of the experimental period was 3 minutes, the participant could end the experiment by sitting on the chair. Two different timing conditions were prepared: reactive and periodic (control) conditions. Under the reactive condition, each action unit was generated reactively to the participant motion, i.e. the chair moved immediately after the participant moved. The participant s motion was detected by using the camera mounted on the ceiling and defined by a threshold value of optical flow. Under the periodic condition, chair s action units were generated at five seconds intervals. All participants participated under both two experimental conditions but the conditions were selected in a counterbalanced order. 3) Procedure: Subjects were allowed to act freely within the experimental area but destruction of the apparatus and equipment of the room was prohibited. This information was given to the subjects before they entered the room. After a subject had entered the room, the experimenter sent a command to initiate the chair motion. During the experiment, the subject was alone in the room and watched by the experimenter through the camera mounted on the ceiling. After the experiment was finished, questionnaires were given to the subjects in another room. The subjects were asked which of Dennett s three stances they took toward the chair during the experiment, giving them a brief example corresponding to each stance. Subjects were then asked to answer a yes or no question in order to test whether the subject attributed goals toward the chair behavior: Did the chair behave in a goal-directed manner? The subject s behavior was recorded using a HDD video recorder connected to a camera on the ceiling in the experimental room. The recordings were the same as what the experimenter saw during the experiment. The video recordings were investigated at a frame rate of 30fps and all of the behaviors exhibited by subjects were classified as the 11 action units listed in Table II. These action units were divided into three main categories - observing, interrupted and probing actions - according to the following criteria: (1) if the subject was concerned with the chair, the action was categorized as an observing action; (2) interrupted actions are subject s actions affected by the chair s actions; and (3) probing actions are those used to investigate the cognitive ability of the chair, testing whether or not the chair could respond to the subject s actions. B. Results Figure 2 shows a behavior sequence typical of the participant who sat on the chair: (1) the subject entered the room, (2) observed and interacted with the chair, and (3) sat on the chair. These pictures were taken by the camera mounted on the ceiling. While 75 percent of subjects sat on the chair under the reactive condition, 63 percent of subjects did so under the periodic condition (see Table III). Under the periodic condi- 3717

4 TABLE III SUCCESS OR FAILURE OF SITTING. sitting rate(%) time for sitting (sec) reactive periodic Fig. 3. Subjects stance toward the chair by condition. Fig. 2. An example of the experiment sequence. tion, subjects took longer than under the reactive condition to sit on the chair. 1) Goal attribution and stance: The McNemar test revealed significant differences in the rate of the stance taken toward the chair s behavior (x 2 (3) = 8.00, p < 0.05), indicating that subjects exposed to the reactive action of the chair had a greater tendency to take the intentional stance than subjects exposed to the periodic action (see Figure 3). A subject reported that the chair just moved randomly under the periodic condition. On the other hand, subjects reported about the chair behavior under the reactive condition as that the chair moved away in order to prevent me from sitting on it and the chair moved toward to me. This indicates that the reactive motion of the chair caused automatic goal attribution to the chair s behavior. While under the reactive condition, 75% of participants attributed goals to the chair motion, 44% of participants did in the periodic condition (see Figure 4). Although one who participated under reactive condition had a tendency to attribute goals to the chair motion, the McNemar test revealed that there was not significant difference (x 2 (1) = 3.20, p = 0.073). 2) Motion analysis: A t-test was performed for the average frequency (per minute) of each action category. The frequencies of all three action categories were significantly higher under the reactive condition than the periodic condition:- observing actions: t = 2.74, p < 0.05; interrupted actions: t = 2.80, p < 0.05; probing actions: t = 2.94, p < 0.05 (see Figure 5). III. EXPERIMENT II In the experiment I, we used a chair as a target of humanrobot interaction. Since a chair has specific appearance according to its function (to be seated), goal attribution would be influenced by its appearance. Thus, in the experiment II, we test the intention attribution tendency with abstract shaped artifact. A. Method Except for the differences described below, the method was the same as in Experiment I. Fig. 4. (a) Observing Fig. 5. Goal attribution for chair behavior. (b) Interrupted (c) Probing Motion analysis result for human-chair interaction. 1) Subjects: Sixteen university students and members of staff participated in the experiment. Subject ages ranged from 21 to 24 years. None had had prior knowledge about the experiment nor experience in interacting with the cube. None had participated in Experiment I. 2) Apparatus and stimuli: The apparatus used in this experiment was the same as in Experiment I except for the appearance. Instead of using a chair as an agent, an abstractshaped object, a 45cm x 45cm x 45cm cube, was used. The cube was made of aluminum, and covered with white acrylic plates. 3) Procedure: In addition to the yes/no question about whether or not the robot behaved in a goal-oriented manner, subjects who answered yes to this question were asked to describe the concrete goal of the cube. B. Results 1) Goal attribution and stance: While under the reactive condition, 81% of participants attributed goals to the cube motion, only 19% of participants did in the periodic condition (see Figure 7). The McNemar test revealed that those participating under the reactive condition attributed goals to 3718

5 Fig. 6. Experimental environment of human-cube interaction. TABLE IV RELATIONSHIP BETWEEN THE STANCES TAKEN BY PARTICIPANTS AND GOAL ATTRIBUTION. Stance goal attribution reactive periodic Intentional Yes 12 3 No 0 0 Design Yes 1 0 No 3 13 Physical Yes 0 0 No 0 0 (a) Observing (b) Interrupted (c) Probing Fig. 9. Motion analysis result for human-cube interaction. Fig. 7. Goal attribution for cube behavior. the chair motion significantly more strongly than under the periodic condition (x 2 (1) = 8.10, p < 0.01). Participants who answered yes to the goal attribution question reported the details of the cube s goal as follows: It reacted to me, It attracted me, and It wanted to tell something. Participants who answered no reported as follows: It represented programmed motion, It ran away from me to attract me, and It ran away after chasing me. Figure 8 shows the stance taken toward cube by subjects under each condition. The number of participants who took the intentional stances under the reactive condition is significantly higher than under the periodic condition (χ 2 (3) = 9.00, p < 0.05). None took the physical stance under either condition. The relationship between the stances taken by participants and goal attribution is shown in Table IV. While all subjects who did not attribute goals to cube behavior took design stance, all except one subject (92%) who attributed goals Fig. 8. Subjects stance taken toward cube. took intentional stance to the cube behavior. In periodic condition, all subjects who did not attribute goals took the design stance and all subjects who attributed goals took the intentional stance. This suggests that even under the periodic condition, taking an intentional stance made subjects attribute goals to cube behavior. 2) Motion analysis: A t-test was performed for the average frequency (per minute) of each action category. The frequencies of all three action categories were significantly higher under the reactive condition than under the periodic condition except for observing action:- observing actions: t = 0.43, p = 0.67; interrupted actions: t = 4.27, p < 0.01; probing actions: t = 2.25, p < 0.05 (see Figure 9). IV. DISCUSSION In both the chair and cube experiments, differences in experimental conditions - reactive vs. periodic - significantly influenced the subject s stance. The reactive movement of both the chair and cube made the subjects take an intentional stance (intention attribution), implying they felt as if they were being observed. This finding replicates our previously-reported result in which a feeling of being looked at, caused by DAD-stimulating actions, made the subject take the intentional stance. Whether the appearance of an artifact represented its functionality or not influenced goal attribution. While in the cube experiment, goal attribution was significantly influenced by the reactive and periodic factors, in the chair experiment, the difference was relatively small; in the chair experiment, subjects participating under either condition had a tendency to attribute goals to chair behavior. One explanation of this difference is that the affordance of the chair - inducing sitting behavior - contributed to goal attribution. Almost all of the subjects in the chair experiment, in fact, sat on the chair within three minutes while the subjects in the cube experiment never touched the cube. 3719

6 The two-way analysis of variance revealed that appearance had a significant effect on action frequency (F = 15.49; p < 0. 01). The action frequency of all action units in the chair experiment is significantly higher than in the cube experiment. This result supports the hypothesis that chair s affordance gave rise to clear goal attribution, suggesting to the subject to attempt bodily interaction with the chair. The result of our motion analysis suggests that frequency of a subject s interaction with a target would be an indicator of the degree of intention attribution. In both experiments, subjects participating under the reactive condition interacted with the artifact more actively than under the periodic condition. This is because taking an intentional stance urged the subject to construe the artifact s behavior in terms of goals. Thus, active interaction with artifacts leads to intention attribution. V. CONCLUSION Our goal is to develop a framework for smooth communication between humans and artifacts, exploiting the human social cognitive ability: theory of mind. The study presented here tested whether reactive movement - implicit representation of attention - could elicit mentalistic attributions from adult humans. Our experiment replicates the finding that whether or not humans can construe the behavior of an artifact in terms of its goal depends upon the subject s stance[16]. Viewing an artifact as an intentional entity causes automatic and obligatory goal attribution and leads to smooth communication between the human and the artifact. Thus making humans treat an artifact as an intentional existence is important for humans to construe and interpret its actions. However, it is not necessary for artifacts to actually have intention or a mental state. The important thing is just to invoke mental state attribution by displaying appropriate cues. 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