scholarly journals Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 71
Author(s):  
Nathan Lucas ◽  
Abhilash Pandya
Keyword(s):  
Task Performance ◽  
Homeland Security ◽  
Human Perception ◽  
Unmanned Vehicles ◽  
Behavior Modeling ◽  
Eye Tracker ◽  
Spatial Frames Of Reference ◽  
Computer Mouse ◽  
Spatially Distributed ◽  
And Behavior

There is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect operators’ ability to integrate information from multiple mobile robots, switch between their spatial frames of reference, and divide attention among many sensory inputs and command outputs. Automation is necessary to help the operator manage increasing demands as the number of robots (and humans) scales up. However, more automation does not necessarily equate to better performance. A generalized robot confidence model was developed, which transforms key operator attention indicators to a robot confidence value for each robot to enable the robots’ adaptive behaviors. This model was implemented in a multirobot test platform with the operator commanding robot trajectories using a computer mouse and an eye tracker providing gaze data used to estimate dynamic operator attention. The human-attention-based robot confidence model dynamically adapted the behavior of individual robots in response to operator attention. The model was successfully evaluated to reveal evidence linking average robot confidence to multirobot search task performance and efficiency. The contributions of this work provide essential steps toward effective human operation of multiple unmanned vehicles to perform spatially distributed and hazardous tasks in complex environments for space exploration, defense, homeland security, search and rescue, and other real-world applications.

Unraveling What’s on Our Minds

2018 ◽  
Author(s):  
Claire M. Zedelius ◽  
Jonathan W. Schooler
Keyword(s):  
Decision Making ◽  
Working Memory ◽  
Task Performance ◽  
Cognitive Processes ◽  
Positive Mood ◽  
Mind Wandering ◽  
Different Types ◽  
And Behavior

Mind-wandering encompasses a variety of different types of thought, involving various different experiential qualities, emotions, and cognitive processes. Much is lost by simply lumping them together, as is typically done in the literature. The goal of this chapter is to explore the nuances that distinguish different types of mind-wandering. The chapter draws on research on mind-wandering as well as other literatures to gain a better understanding of how these different types of mind-wandering affect cognition and behavior. It specifically discusses the distinct effects of different types of mind-wandering on task performance, working memory, mood, and creativity. Finally, the chapter discusses the idea of deliberate engagement in particular types of mind-wandering as a way to achieve desirable outcomes, such as maintaining a positive mood, enhancing creativity, or aiding decision-making.

Artificial intelligence in psychology: How can we enable psychology students to accept and use artificial intelligence?

2021 ◽  
pp. 147572572110371
Author(s):  
Sabrina Gado ◽  
Regina Kempen ◽  
Katharina Lingelbach ◽  
Tanja Bipp
Keyword(s):  
Artificial Intelligence ◽  
Technology Acceptance ◽  
Human Perception ◽  
Psychology Students ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Technology Acceptance Models ◽  
Psychological Training ◽  
Acceptance Model ◽  
And Behavior

Psychologists with their expertise in statistics and regarding human perception and behavior can contribute valuable insights to the development of innovative and useful artificial intelligence (AI) systems. Therefore, we need to raise attention and curiosity for AI and foster the willingness to engage with it among psychology students. This requires identifying approaches to integrate a general understanding of AI technology into formal psychological training and education. This study investigated to what extent psychology students currently accept and use AI and what affects their perception and usage. Therefore, an AI acceptance model based on established technology acceptance models was developed and tested in a sample of 218 psychology students. An acceptable fit with the data was found for an adapted version. Perceived usefulness and ease of use were most predictive for the students’ attitude towards AI; attitude itself, as well as perceived usefulness, social norm, and perceived knowledge, were predictors for the intention to use AI. In summary, we identified relevant factors for designing AI training approaches in psychology curricula. In this way, possible restraints regarding the use of AI can be reduced and its beneficial opportunities exploited in psychological contexts.

From Smart Concept to Desired Experiences

2020 ◽  
pp. 154-168
Author(s):  
Cristina Caramelo Gomes
Keyword(s):  
Built Environment ◽  
Smart Cities ◽  
Human Perception ◽  
Spatial Relations ◽  
Functional Orientation ◽  
And Behavior

The development and implementation of ICT solutions changed the built environment. Objects from daily human routines and services, while aiming for sustainable and inclusive qualified solutions, challenged the countless possibilities of interaction between individuals, individuals and products, and products and products. Smart cities associate intelligence to environments and products to boost functionalities, uses, and experiences. The design of smart cities, from the spatial relations, objects interactions, and services availability must be user oriented to satisfy users' needs and expectations, while promoting qualified experiences. From real and questionable solutions, due to technical or functional orientation, emerges the need to observe human perception, reaction, and behavior to understand how it is possible to improve the experience. The aim of this chapter is to highlight the need of a different approach to the conceptualization of smart cities, environments, products, and services, emphasizing an emotionally appealing experience.

Distinguished Scholars Invited Essay: Becoming a Good Sport and a Better Performer: A Social Information Processing View of Authentic Leadership

2017 ◽  
Vol 25 (2) ◽  
pp. 141-152
Author(s):  
Chester A. Schriesheim ◽  
Yonghong Liu
Keyword(s):  
Information Processing ◽  
Task Performance ◽  
Social Information Processing ◽  
High Performance ◽  
Authentic Leadership ◽  
Social Information ◽  
Social Information Processing Theory ◽  
Processing Theory ◽  
Contrast Analysis ◽  
And Behavior

Drawing on social information processing theory, this study investigates the mechanisms by which authentic leadership affects subordinate task performance through subordinate attitudes and behavior. Sportsmanship, conceptualized as a behavioral indicator of employee positivity and persistence in pursuing high performance, is argued to be a potentially important outcome for authentic leadership. Data collected from 203 matched subordinate–supervisor dyads in six organizations from six diverse industries were subjected to contrast analysis with bootstrapping. The results suggest that the indirect effect of authentic leadership on subordinate sportsmanship is mainly via a cognitive process, as opposed to an affective one. Furthermore, it is the employee’s sportsmanship that transmits the effects of authentic leadership on employee task performance. Implications and future directions are discussed.

An approach for emotions and behavior modeling in a crowd in the presence of rare events

2016 ◽  
Vol 24 (6) ◽  
pp. 428-445 ◽  
Author(s):  
Lynda Saifi ◽  
Abdelhak Boubetra ◽  
Farid Nouioua
Keyword(s):  
Probability Theory ◽  
Walking Speed ◽  
Behavior Modeling ◽  
Personality Factors ◽  
Common Phenomenon ◽  
Pedestrian Flow ◽  
Behavioral Rules ◽  
Emotional Model ◽  
The Right ◽  
And Behavior

A common phenomenon in everyday life is that, when a strange event occurs or is announced, a regular crowd can completely change, showing different intense emotions and sometimes uncontrollable and violent emerging behavior. These emotions and behaviors that disturb the organization of a crowd are of concern in our study, and we attempt to predict these suspicious circumstances and provide help in making the right decisions at the right time. Furthermore, most of the models that address crowd disasters belong to the physical or the cognitive approaches. They study pedestrian flow and collision avoidance, etc., and they use walking speed and angle of vision. However, in this work, based on a behavioral rules approach, we aim to model emergent emotion, behavior and influence in a crowd, taking into account particularly the personality of members of the crowd. For this purpose, we have combined the OCEAN (Openness, Consciousness, Extraversion, Agreeableness, and Neuroticism) personality model with the OCC (Ortony, Clore, and Collins) emotional model to indicate the susceptibility of each of the five personality factors to feeling every emotion. Then we proposed an approach that uses first fuzzy logic for the emotional modeling of critical emotions of members of the crowd at the announcement or the presence of unusual events, in order to quantify emotions. Then, we model the behavior and the tendency towards actions using probability theory. Finally, the influence among the members of the crowd is modeled using the neighborhood principle and cellular automata.

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