scholarly journals Predicting children’s and adults’ preferences in physical interactions via physics simulation

2021 ◽  
Author(s):  
George Kachergis ◽  
Samaher Radwan ◽  
Bria Long ◽  
Judith Fan ◽  
Michael Lingelbach ◽  
...  
Keyword(s):  
Human Behavior ◽  
Computational Models ◽  
Strong Preference ◽  
Artificial Agents ◽  
Experimental Paradigm ◽  
Simulated Environment ◽  
Physics Simulation ◽  
Physical Simulations ◽  
Physical Interactions ◽  
Support Relations

Curiosity is a fundamental driver of human behavior, and yet because of its open-ended nature and the wide variety of behaviors it inspires in different contexts, it is remarkably difficult to study in a laboratory context. A promising approach to developing and testing theories of curiosity is to instantiate them in artificial agents that are able to act and explore in a simulated environment, and then compare the behavior of these agents to humans exploring the same stimuli. Here we propose a new experimental paradigm for examining children’s – and AI agents’ – curiosity about objects’ physical interactions. We let them choose which object to drop another object onto in order to create the most interesting effect. We compared adults’ (N=155) and children’s choices (N=66; 3-7 year-olds) and found that both children and adults show a strong preference for choosing target objects that could potentially contain the dropped object. Adults alone also make choices consistent with achieving support relations. We contextualize our results using heuristic computational models based on 3D physical simulations of the same scenarios judged by participants.

scholarly journals A computational reward learning account of social media engagement

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Björn Lindström ◽  
Martin Bellander ◽  
David T. Schultner ◽  
Allen Chang ◽  
Philippe N. Tobler ◽  
...  
Keyword(s):  
Social Media ◽  
Human Behavior ◽  
Computational Models ◽  
Average Rate ◽  
Human Life ◽  
Modern Human ◽  
Reward Learning ◽  
Learning Mechanisms ◽  
Social Media Engagement ◽  
Social Rewards

AbstractSocial media has become a modern arena for human life, with billions of daily users worldwide. The intense popularity of social media is often attributed to a psychological need for social rewards (likes), portraying the online world as a Skinner Box for the modern human. Yet despite such portrayals, empirical evidence for social media engagement as reward-based behavior remains scant. Here, we apply a computational approach to directly test whether reward learning mechanisms contribute to social media behavior. We analyze over one million posts from over 4000 individuals on multiple social media platforms, using computational models based on reinforcement learning theory. Our results consistently show that human behavior on social media conforms qualitatively and quantitatively to the principles of reward learning. Specifically, social media users spaced their posts to maximize the average rate of accrued social rewards, in a manner subject to both the effort cost of posting and the opportunity cost of inaction. Results further reveal meaningful individual difference profiles in social reward learning on social media. Finally, an online experiment (n = 176), mimicking key aspects of social media, verifies that social rewards causally influence behavior as posited by our computational account. Together, these findings support a reward learning account of social media engagement and offer new insights into this emergent mode of modern human behavior.

scholarly journals Chapter 9 - Theory of Mind and Joint Attention - The Handbook on Socially Interactive Agents

2021 ◽  
Author(s):  
Jairo Pérez-Osorio ◽  
Eva Wiese ◽  
Agnieszka Wykowska
Keyword(s):  
Theory Of Mind ◽  
Joint Attention ◽  
Cognitive Neuroscience ◽  
Computational Models ◽  
Social Cognitive ◽  
Virtual Agents ◽  
Artificial Agents ◽  
Future Directions ◽  
Social Cognitive Neuroscience ◽  
Intelligent Virtual Agents

The present chapter provides an overview from the perspective of social cognitive neuroscience (SCN) regarding theory of mind (ToM) and joint attention (JA) as crucial mechanisms of social cognition and discusses how these mechanisms have been investigated in social interaction with artificial agents. In the final sections, the chapter reviews computational models of ToM and JA in social robots (SRs) and intelligent virtual agents (IVAs) and discusses the current challenges and future directions.

Peri-personal space as an interface for self-environment interaction

2021 ◽  
pp. 17-46
Author(s):  
Jean-Paul Noel ◽  
Tommaso Bertoni ◽  
Andrea Serino
Keyword(s):  
Motor System ◽  
Computational Models ◽  
Multisensory Processing ◽  
Critical Role ◽  
Personal Space ◽  
Environment Interaction ◽  
Specific System ◽  
Physical Interactions ◽  
Psychophysical Studies ◽  
The Brain

The brain has developed a specific system to encode the space closely surrounding our body, our peri-personal space (PPS). This space is the theatre where all physical interactions with objects in the environment occur, and thus is postulated to play a critical role in both approaching and defensive behaviour. Here, we first describe the classic neurophysiological findings that have led researchers to conceive of PPS as a multisensory-motor interface. This historical perspective is given to clarify what properties are strictly related to PPS encoding, and what characteristics bear out or are related to PPS. Then, in an effort to uncover gaps in knowledge that often go unnoticed, we critically examine the association between PPS and i) multisensory processing, and ii) the motor system—its strongest allies. We do not mean to say that PPS isn’t multisensory-motor, simply to pinpoint current research shortcomings. Subsequently, we detail more recent psychophysical studies, highlighting the extreme plasticity of PPS, and its putative role in bodily self-consciousness and social cognition. Lastly, we briefly discuss computational models of PPS. Throughout the chapter, we particularly attempt to emphasize open areas of investigation. By critically evaluating past findings, many of them our own, we hope to provide a forward-looking perspective on the study of PPS.

Construction of Meanings in Biological and Artificial Agents

2009 ◽  
pp. 139-157
Author(s):  
Martin Takác
Keyword(s):  
Vertical Transmission ◽  
Computational Models ◽  
Necessary Conditions ◽  
Design Principles ◽  
Meaning Construction ◽  
Mechanisms Of Action ◽  
Artificial Agents ◽  
Evolutionary Context ◽  
Living Organisms

In this chapter, we focus on the issue of understanding in various types of agents. Our main goal is to build up notions of meanings and understanding in neutral and non-anthropocentric terms that would not exclude preverbal living organisms and artificial systems by definition. By analyzing the evolutionary context of understanding in living organisms and the representation of meanings in several artificially built systems, we come to design principles for building “understanding” artificial agents and formulate necessary conditions for the presence of inherent meanings. Such meanings should be based on interactional couplings between the agents and their environment, and should help the agents to orient themselves in the environment and to satisfy their goals. We explore mechanisms of action-based meaning construction, horizontal coordination, and vertical transmission of meanings and exemplify them with computational models.

Implementing a modeling software for animated protein-complex interactions using a physics simulation library

2014 ◽  
Vol 12 (06) ◽  
pp. 1442003 ◽  
Author(s):  
Yutaka Ueno ◽  
Shuntaro Ito ◽  
Akihiko Konagaya
Keyword(s):  
Three Dimensional ◽  
Rigid Body Dynamics ◽  
Dynamics Simulation ◽  
Molecular Models ◽  
Body Dynamics ◽  
Physics Simulation ◽  
Modeling Software ◽  
Physical Simulations ◽  
A Cell ◽  
Scripting Language

To better understand the behaviors and structural dynamics of proteins within a cell, novel software tools are being developed that can create molecular animations based on the findings of structural biology. This study proposes our method developed based on our prototypes to detect collisions and examine the soft-body dynamics of molecular models. The code was implemented with a software development toolkit for rigid-body dynamics simulation and a three-dimensional graphics library. The essential functions of the target software system included the basic molecular modeling environment, collision detection in the molecular models, and physical simulations of the movement of the model. Taking advantage of recent software technologies such as physics simulation modules and interpreted scripting language, the functions required for accurate and meaningful molecular animation were implemented efficiently.

Would You Deliver an Electric Shock in 2015? Obedience in the Experimental Paradigm Developed by Stanley Milgram in the 50 Years Following the Original Studies

2017 ◽  
Vol 8 (8) ◽  
pp. 927-933 ◽  
Author(s):  
Dariusz Doliński ◽  
Tomasz Grzyb ◽  
Michał Folwarczny ◽  
Patrycja Grzybała ◽  
Karolina Krzyszycha ◽  
...  
Keyword(s):  
Human Behavior ◽  
Electric Shock ◽  
Turning Point ◽  
Personality Characteristics ◽  
Experimental Paradigm ◽  
Ethical Considerations ◽  
Stanley Milgram

In spite of the over 50 years which have passed since the original experiments conducted by Stanley Milgram on obedience, these experiments are still considered a turning point in our thinking about the role of the situation in human behavior. While ethical considerations prevent a full replication of the experiments from being prepared, a certain picture of the level of obedience of participants can be drawn using the procedure proposed by Burger. In our experiment, we have expanded it by controlling for the sex of participants and of the learner. The results achieved show a level of participants’ obedience toward instructions similarly high to that of the original Milgram studies. Results regarding the influence of the sex of participants and of the “learner,” as well as of personality characteristics, do not allow us to unequivocally accept or reject the hypotheses offered.

Trust of Simulated Robotic Peacekeepers among Resident and Expatriate Americans

2017 ◽  
Vol 61 (1) ◽  
pp. 2091-2095 ◽  
Author(s):  
Shelby K. Long ◽  
Nicole D. Karpinsky ◽  
James P. Bliss
Keyword(s):  
United States ◽  
Human Behavior ◽  
The United States ◽  
The Past ◽  
Simulated Environment ◽  
Military Applications ◽  
China And Japan

Researchers have heavily debated the definition and role of trust in human behavior over the past few decades. As robots begin to be used more often, particularly in international military applications, understanding human-robot trust becomes increasingly important. The current study aims to investigate trust differences in robotic peacekeepers between Americans living in the United States, China, and Japan using a simulated environment. We predicted that trust in robots would differ as a function of culture. Results showed that Americans residing in Japan were significantly more trusting than Americans in the United States or China overall. Further, Americans living in America trusted robotic peacekeepers significantly more than Americans residing in China. This suggests that people who adopt a certain trust framework are those who have chosen to live abroad, but more research is needed to understand the differences between resident and expatriate Americans.

READING COMPLEXITY IN CHUA'S OSCILLATOR THROUGH MUSIC. PART I: A NEW WAY OF UNDERSTANDING CHAOS

2005 ◽  
Vol 15 (02) ◽  
pp. 253-382 ◽  
Author(s):  
ELEONORA BILOTTA ◽  
STEFANIA GERVASI ◽  
PIETRO PANTANO
Keyword(s):  
Dynamical System ◽  
Dynamical Systems ◽  
Human Behavior ◽  
Computational Models ◽  
Human Subjects ◽  
Equilibrium Points ◽  
Dynamical Behavior ◽  
Modern Science ◽  
Qualitative Behavior ◽  
Chua’S Oscillator

Modern Science is finding new methods of looking at biological, physical or social phenomena. Traditional methods of quantification are no longer sufficient and new approaches are emerging. These approaches make it apparent that the phenomena the observer is looking at are not classifiable by conventional methods. These phenomena are complex. A complex system, as Chua's oscillator, is a nonlinear configuration whose dynamical behavior is chaotic. Chua's oscillator equations allow to define the basic behavior of a dynamical system and to detect the changes in the qualitative behavior of a system when bifurcation occurs, as parameters are varied. The typical set of behavior of a dynamical system can be detailed as equilibrium points, limit cycles, strange attractors. The concepts, methods and paradigms of Dynamical Systems Theory can be applied to understand human behavior. Human behavior is emergent and behavior patterns emerge thanks to the way the parts or the processes are coordinated among themselves. In fact, the listening process in humans is complex and it develops over time as well. Sound and music can be both inside and outside humans. This tutorial concerns the translation of Chua's oscillators into music, in order to find a new way of understanding complexity by using music. By building up many computational models which allow the translation of some quantitative features of Chua's oscillator into sound and music, we have created many acoustical and musical compositions, which in turn present the characteristics of dynamical systems from a perceptual point of view. We have found interesting relationships between dynamical systems behavior and their musical translation since, in the process of listening, human subjects perceive many of the structures as possible to perceive in the behavior of Chua's oscillator. In other words, human cognitive abilities can analyze the large and complicated patterns produced by Chua's systems translated into music, achieving the cognitive economy and the coordination and synthesis of countless data at our disposal that occur in the perception of dynamic events in the real world. Music can be considered the semantics of dynamical systems, which gives us a powerful method for interpreting complexity.

Crash Cart Usability: A Method in Simulation & Iterative Design

2021 ◽  
Vol 10 (1) ◽  
pp. 99-102
Author(s):  
Matthew N. Jesso ◽  
Yuhao Peng ◽  
Amanda Anderson
Keyword(s):  
Clinical Staff ◽  
Time On Task ◽  
Front Line ◽  
Iterative Design ◽  
Simulated Environment ◽  
Qualitative Feedback ◽  
Design Cycle ◽  
Physical Interactions

Prior to implementation, front line clinical staff assessed a new crash cart in a simulated environment. The contents of the cart were assessed during a simulated code on a number of metrics; time on task, number of physical interactions, errors, as well as qualitative feedback from participants. These metrics helped researchers redesign the cart contents to improve visibility and organization of supplies. Using an iterative design cycle, the redesign cart and contents showed a reduction in time on task, physical interactions, and errors for most scenarios.

scholarly journals Large prospective losses lead to sub-optimal sensorimotor decisions in humans

2018 ◽  
Author(s):  
Tyler J. Adkins ◽  
Richard L. Lewis ◽  
Taraz G. Lee
Keyword(s):  
Bounded Rationality ◽  
Recent Work ◽  
Human Behavior ◽  
Strong Evidence ◽  
Decision Problem ◽  
Computational Models ◽  
Cognitive Biases ◽  
Expected Gain ◽  
Potential Losses ◽  
Biases And Heuristics

AbstractThe rationality of human behavior has been a major problem in philosophy for centuries. The pioneering work of Kahneman and Tversky provides strong evidence that people are not rational. Recent work in psychophysics argues that incentivized sensorimotor decisions (such as deciding where to reach to get a reward) maximizes expected gain, suggesting that it may be impervious to cognitive biases and heuristics. We rigorously tested this hypothesis using multiple experiments and multiple computational models. We obtained strong evidence that people deviated from the objectively rational strategy when potential losses were large. They instead appeared to follow a strategy in which they simplify the decision problem and satisfice rather than optimize. This work is consistent with the framework known as bounded rationality, according to which people behave rationally given their computational limitations.

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