Perception of intentions and mental states in autonomous virtual agents.
Journal of Vision(2011)
摘要
Perception of intentions and mental states in autonomous virtual agents Peter C. Pantelis, Steven Cholewiak, Paul Ringstad, Kevin Sanik, Ari Weinstein, Chia-Chien Wu, Jacob Feldman (petercp@eden.rutgers.edu, jacob@ruccs.rutgers.edu) Departments of Psychology, Center for Cognitive Science, Rutgers University-New Brunswick 152 Frelinghuysen Road, Piscataway, NJ 08854 USA Abstract 1995; Johnson, 2000). But the adult capacity to understand animate motion in terms of intelligent behavior has been re- searched less. Computational approaches to the problem of intention estimation are still scarce (Baker, Tenenbaum, \u0026 Saxe, 2006; Feldman \u0026 Tremoulet, 2008), in part because of the difficulty in specifying the problem in computational terms. Almost without exception, video stimuli used in past ex- periments in this area have consisted of hand-crafted an- imations with motions chosen subjectively by the experi- menters in order to achieve particular psychological impres- sions (Porter \u0026 Susman, 2000). This makes it difficult to in- vestigate the way subjects estimate intentionality, because the object of the estimation procedure—the actual mental state of the agent under observation—does not actually exist. Our proposed solution to this problem is to indeed endow our stimuli agents with “minds,” which our subjects then attempt to “read.” Comprehension of goal-directed, intentional motion is an im- portant but understudied visual function. To study it, we created a two-dimensional virtual environment populated by independently-programmed autonomous virtual agents, which navigate the environment, collecting food and competing with one another. Their behavior is modulated by a small number of distinct “mental states”: exploring, gathering food, attacking, and fleeing. In two experiments, we studied subjects’ ability to detect and classify the agents’ continually changing men- tal states on the basis of their motions and interactions. Our analyses compared subjects’ classifications to the ground truth state occupied by the observed agent’s autonomous program. Although the true mental state is inherently hidden and must be inferred, subjects showed both high validity (correlation with ground truth) and high reliability (correlation with one an- other). The data provide intriguing evidence about the factors that influence estimates of mental state—a key step towards a true “psychophysics of intention.” Keywords: animate motion perception; theory of mind; inten- tionality; action understanding; goal inference. Introduction Comprehension of the goals and intentions of other intelligent agents is an essential aspect of cognition. Motion is an espe- cially important cue to intention, as vividly illustrated by the famous short film by Heider and Simmel (1944). The “cast” of this film consists only of two triangles and a circle, but the motions of these simple geometrical figures are universally interpreted in terms of dramatic narrative. Indeed, it is practi- cally impossible to understand many naturally occurring mo- tions without comprehending the intentions that helped cause them: a person running is interpreted as trying to get some- where; a hand lifting a Coke can is automatically understood as a person intending to raise the can, not simply as two ob- jects moving upwards together (Mann, Jepson, \u0026 Siskind, 1997). Much of the motion in a natural environment—and certainly some of the most behaviorally important motion— is caused by other agents, and is impossible to understand except in terms of how and why they might have caused it. Human subjects readily attribute mentality and goal- directedness to moving objects as a function of properties of their motion (Tremoulet \u0026 Feldman, 2000), and in par- ticular on how that motion seems to relate to the motion of other agents and objects in the environment (Blythe, Todd, \u0026 Miller, 1999; Dittrich \u0026 Lea, 1994; Gao, McCarthy, \u0026 Scholl, 2010; Pantelis \u0026 Feldman, 2010; Tremoulet \u0026 Feld- man, 2006; Zacks, Kumar, Abrams, \u0026 Mehta, 2009). The broad problem of attributing mentality to others has received a great deal of attention in the philosophical literature (of- ten under the term mindreading), and has been most widely studied in infants and children (Gelman, Durgin, \u0026 Kaufman, A virtual environment of autonomous agents We developed a two-dimensional interactive virtual envi- ronment populated with autonomous virtual agents (Fig. 1). These agents (referred to as Independent Mobile Personali- ties, or IMPs), are simple but cognitively independent virtual robots, equipped with perception, planning, decision making, and goals. They move about in the virtual environment, in- teracting with each other, making intelligent though unpre- dictable decisions and taking steps to achieve simple goals. The IMPs are endowed with potentially distinct personalities and cognitive faculties, including variations in intelligence, memory, aggression, and strategy. The result is a complex, dynamic microcosm in which goal-directed behavior, and the perception thereof, can be studied in a controlled way. The inspiration is taken from the substantial literature on artificial life (Shao \u0026 Terzopoulos, 2007; Yaeger, 1994) in which inter- actions among virtual creatures have been extensively mod- eled. But unlike previous environments, our agents are cog- nitively complete, meaning that their behavior is entirely de- termined by autonomous decisions based on input they have received via their own senses, and are presented visually to subjects so that we may study how their intentions are inter- preted by observers. Our focus is on what can be understood from the IMPs’ motion alone; to this end, we depict the IMPs as triangles, so that they have clearly identifiable main axes and front ends, but otherwise minimal shape. Because we have direct access to the “actual” intentions and mental states of the agents—represented by a simple state variable in the autonomous program—we can compare this “ground truth”
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