Parameterizing mental model ascription across intelligent agents

2014 ◽  
Vol 15 (3) ◽  
pp. 404-425 ◽  
Author(s):  
Marjorie McShane
Keyword(s):  
Social Interactions ◽  
Intelligent Agents ◽  
Mental Model ◽  
Mental States ◽  
Virtual Patient ◽  
Prototype System ◽  
Virtual Patients ◽  
Artificial Intelligent ◽  
Value Sets ◽  
Real Patients

Mental model ascription – also called mindreading – is the process of inferring the mental states of others, which happens as a matter of course in social interactions. But although ubiquitous, mindreading is presumably a highly variable process: people mindread to different extents and with different results. We hypothesize that human mindreading ability relies on a large number of personal and contextual features: the inherent abilities of specific individuals, their current physical and mental states, their knowledge of the domain of discourse, their familiarity with the interlocutor, the risks associated with an incorrect assessment of intent, and so on. This paper presents a theory of mindreading that models diverse artificial intelligent agents using an inventory of parameters and value sets that represent traits of humans and features of discourse contexts. Examples are drawn from Maryland Virtual Patient, a prototype system that will permit medical trainees to diagnose and treat cognitively modeled virtual patients with the optional assistance of a virtual tutor. Since real patients vary greatly with respect to physiological and cognitive features, so must a society of virtual patients. Modeling such variation is one of the goals of the overall OntoAgent program of research and development.

scholarly journals The ratio of the mental and delinquent model of adolescent behaviour

2020 ◽  
Vol 26 (3) ◽  
pp. 73-78
Author(s):  
Yelena V. Gartvik
Keyword(s):  
Empirical Study ◽  
Social Interactions ◽  
Mental Model ◽  
Psychological Factors ◽  
Mental States ◽  
Personality Characteristics ◽  
Delinquent Behaviour ◽  
The Family ◽  
Adolescent Behaviour ◽  
The Individual

At present, the identification of psychological factors as a determinant of the illegal behaviour of adolescents is of great importance. The mental model allows explaining and predicting the behaviour of other people and reflecting one’s own mental inner reality. The study of the mental model in adolescents with delinquent and law-abiding behaviour using specially designed narratives provided us with the opportunity to analyse the understanding by adolescents, who have committed and not committed crimes, of the mental states of their own and that of another person, as well as the causes of such states in the process of social interactions. The ability to understand the mental world is paramount and necessary for understanding social interactions, for the correct formation of motives and semantic attitudes of the individual. The results of an empirical study allowed us to confirm the hypothesis that the deficit of the mental model is formed in the family; it is associated with the personality characteristics of the adolescent and, obviously, affects the formation of delinquent behaviour.

scholarly journals Evaluating the Difference between Virtual and Paper-Based Clinical Cases in Family Medicine Undergraduate Education

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Zalika Klemenc-Ketis ◽  
Branka Cagran ◽  
Dejan Dinevski
Keyword(s):  
Family Medicine ◽  
Virtual Patient ◽  
Educational Outcome ◽  
Factual Knowledge ◽  
Virtual Patients ◽  
Multiple Choice Questions ◽  
Significant Difference ◽  
The Difference ◽  
And Control ◽  
Clinical Cases

Introduction. A “virtual patient” is defined as a computer program which simulates real patients’ cases. The aim of this study was to determine whether the inclusion of virtual patients affects the level of factual knowledge of family medicine students at the undergraduate level. Methods. This was a case-controlled prospective study. The students were randomly divided into experimental (EG: N=51) and control (CG: N=48) groups. The students in the EG were asked to practice diagnosis using virtual patients instead of the paper-based clinical cases which were solved by the students in the CG. The main observed variable in the study was knowledge of family medicine, determined by 50 multiple choice questions (MCQs) about knowledge of family medicine. Results. There were no statistically significant differences in the groups’ initial knowledge. At the final assessment of knowledge, there were no statistically significant differences between the groups, but there was a statistically significant difference between their initial and final knowledge. Conclusions. The study showed that adding virtual patient cases to the curriculum, instead of paper clinical cases, did not affect the level of factual knowledge about family medicine. Virtual patients can be used, but a significant educational outcome is not expected.

scholarly journals Human agency beliefs influence behaviour during virtual social interactions

2017 ◽  
Author(s):  
Nathan Caruana ◽  
Dean Spirou ◽  
Jon Brock
Keyword(s):  
Social Interactions ◽  
Subjective Experience ◽  
Eye Contact ◽  
Human Agency ◽  
Mental States ◽  
Human Condition ◽  
Human Interaction ◽  
Intentional Stance ◽  
Agency Beliefs ◽  
The Impact

In recent years, with the emergence of relatively inexpensive and accessible virtual reality technologies, it is now possible to deliver compelling and realistic simulations of human-to-human interaction. Neuroimaging studies have shown that, when participants believe they are interacting via a virtual interface with another human agent, they show different patterns of brain activity compared to when they know that their virtual partner is computer-controlled. The suggestion is that users adopt an “intentional stance” by attributing mental states to their virtual partner. However, it remains unclear how beliefs in the agency of a virtual partner influence participants’ behaviour and subjective experience of the interaction. We investigated this issue in the context of a cooperative “joint attention” game in which participants interacted via an eye tracker with a virtual onscreen partner, directing each other’s eye gaze to different screen locations. Half of the participants were correctly informed that their partner was controlled by a computer algorithm (“Computer” condition). The other half were misled into believing that the virtual character was controlled by a second participant in another room (“Human” condition). Those in the “Human” condition were slower to make eye contact with their partner and more likely to try and guide their partner before they had established mutual eye contact than participants in the “Computer” condition. They also responded more rapidly when their partner was guiding them, although the same effect was also found for a control condition in which they responded to an arrow cue. Results confirm the influence of human agency beliefs on behaviour in this virtual social interaction context. They further suggest that researchers and developers attempting to simulate social interactions should consider the impact of agency beliefs on user experience in other social contexts, and their effect on the achievement of the application’s goals.

Supporting Social Interactions In Human-Ai Teams: Profiling Human Teammates From Sparse Data

2021 ◽  
Vol 65 (1) ◽  
pp. 665-669
Author(s):  
Rhyse Bendell ◽  
Jessica Williams ◽  
Stephen M. Fiore ◽  
Florian Jentsch
Keyword(s):  
Artificial Intelligence ◽  
Social Cognition ◽  
Social Interactions ◽  
Team Performance ◽  
Intelligent Agents ◽  
Social Intelligence ◽  
Social Cognitive ◽  
Social Cues ◽  
Cognitive Mechanisms ◽  
Human Agent

Artificial intelligence has been developed to perform all manner of tasks but has not gained capabilities to support social cognition. We suggest that teams comprised of both humans and artificially intelligent agents cannot achieve optimal team performance unless all teammates have the capacity to employ social-cognitive mechanisms. These form the foundation for generating inferences about their counterparts and enable execution of informed, appropriate behaviors. Social intelligence and its utilization are known to be vital components of human-human teaming processes due to their importance in guiding the recognition, interpretation, and use of the signals that humans naturally use to shape their exchanges. Although modern sensors and algorithms could allow AI to observe most social cues, signals, and other indicators, the approximation of human-to-human social interaction -based upon aggregation and modeling of such cues is currently beyond the capacity of potential AI teammates. Partially, this is because humans are notoriously variable. We describe an approach for measuring social-cognitive features to produce the raw information needed to create human agent profiles that can be operated upon by artificial intelligences.

Learner Acceptance of Using Virtual Patient Encounters to Train Foreign Healthcare Professionals in Swedish

2017 ◽  
pp. 379-393
Author(s):  
Uno G. H. Fors ◽  
Olivier Courteille
Keyword(s):  
Learning Environments ◽  
Communication Skills ◽  
Healthcare Professionals ◽  
Virtual Patient ◽  
Patient Communication ◽  
Virtual Patients ◽  
Educational Value ◽  
Good Communication ◽  
Professional Needs ◽  
Almost All

Healthcare professionals need good communication skills to be able to communicate with patients. In such provider-patient communication, the professional needs to be well understood by the patient, but also be able to understand subtle parts of a medical history taking dialogue with worried, sick or mentally affected patients. Virtual Patients (VPs) – learning environments that simulate encounters between a patient and a physician – were used to prepare 26 immigrating professionals in Swedish for healthcare practitioners. The professionals were speaking nine different foreign languages and used two different VP systems to train patient communication. Almost all participants welcomed the use of VPs for training communication in healthcare Swedish and 19 of the 26 users indicated that they considered that VPs should be mandatory to use in future courses. Targeted individual training in provider-patient communication with Virtual Patients seems to be of great educational value and well accepted by immigrating healthcare professionals.

Agents with a Theory of Mind in Virtual Training

2011 ◽  
pp. 172-187
Author(s):  
Maaike Harbers ◽  
Karel van den Bosch ◽  
John-Jules Ch. Meyer
Keyword(s):  
Social Interaction ◽  
Social Behavior ◽  
Theory Of Mind ◽  
Crisis Management ◽  
Intelligent Agents ◽  
Effective Means ◽  
Mental States ◽  
Complex Dynamic ◽  
Virtual Training ◽  
Effective Training

Virtual training provides an effective means to train complex, dynamic tasks like social interaction, negotiation and crisis management. The virtual characters with whom the trainee interacts are often played by autonomous, intelligent agents. For effective training, it is required that the agents behave in a believable way. In order to display believable social behavior, the agents must be able to take others’ perspectives into account. This can be achieved by equipping them with a theory of mind, that is, the ability to attribute mental states such as beliefs and desires to others. In this chapter the authors describe an executable model for agents with a theory of mind, based on the BDI (belief desire intention) approach. The aim of the model is to develop agents that display believable social behavior and provide explanations about their behavior.

The Exploration of Autonomous Vehicles

2022 ◽  
pp. 930-944
Author(s):  
Anthony J. Gephardt ◽  
Elizabeth Baoying Wang
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Intelligent Agents ◽  
Autonomous Vehicles ◽  
Learning Processes ◽  
Artificial Intelligent ◽  
The World ◽  
History Of ◽  
The Creation

This chapter explores the world of autonomous vehicles. Starting from the beginning, it covers the history of the automobile dating back to 1769. It explains how the first production automobile came about in 1885. The chapter dives into the history of auto safety, ranging from seatbelts to full-on autonomous features. One of the main focuses is the creation and implementation of artificial intelligent (AI), neural networks, intelligent agents, and deep Learning Processes. Combining the hardware on the vehicle with the intelligence of AI creates what we know as autonomous vehicles today.

scholarly journals Automatic analysis of summary statements in virtual patients - a pilot study evaluating a machine learning approach

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Inga Hege ◽  
Isabel Kiesewetter ◽  
Martin Adler
Keyword(s):  
Language Processing ◽  
Virtual Patient ◽  
Global Rating ◽  
Virtual Patients ◽  
Immediate Feedback ◽  
Assessment Scores ◽  
Reasoning Abilities ◽  
Reliable Assessment ◽  
Machine Learning Approach ◽  
Computer Based

Abstract Background The ability to compose a concise summary statement about a patient is a good indicator for the clinical reasoning abilities of healthcare students. To assess such summary statements manually a rubric based on five categories - use of semantic qualifiers, narrowing, transformation, accuracy, and global rating has been published. Our aim was to explore whether computer-based methods can be applied to automatically assess summary statements composed by learners in virtual patient scenarios based on the available rubric in real-time to serve as a basis for immediate feedback to learners. Methods We randomly selected 125 summary statements in German and English composed by learners in five different virtual patient scenarios. Then we manually rated these statements based on the rubric plus an additional category for the use of the virtual patients’ name. We implemented a natural language processing approach in combination with our own algorithm to automatically assess 125 randomly selected summary statements and compared the results of the manual and automatic rating in each category. Results We found a moderate agreement of the manual and automatic rating in most of the categories. However, some further analysis and development is needed, especially for a more reliable assessment of the factual accuracy and the identification of patient names in the German statements. Conclusions Despite some areas of improvement we believe that our results justify a careful display of the computer-calculated assessment scores as feedback to the learners. It will be important to emphasize that the rating is an approximation and give learners the possibility to complain about supposedly incorrect assessments, which will also help us to further improve the rating algorithms.

An Intelligent Human-Computer Collaborative Method for Creative Design

2014 ◽  
Vol 644-650 ◽  
pp. 3235-3240
Author(s):  
Jian Wei Wang
Keyword(s):  
Cognitive Psychology ◽  
Creative Thinking ◽  
Space Exploration ◽  
Prototype System ◽  
Creative Design ◽  
Collaborative Model ◽  
Artificial Intelligent ◽  
Key Technologies ◽  
Body Design ◽  
Intelligent Models

Two intelligent models for creative thinking, which are conceptual restructuring and space exploration, are studied based on artificial intelligent and cognitive psychology. The characteristics of the models and their applications are analyzed. A human-computer collaborative creative model is presented, which combines the nonlogical creation typified by conceptual restructuring, and logic creation typified by space exploration on the basis of visualization. The human-computer collaborative model for product creative design is also proposed, and the key technologies for realizing the human-computer collaboration for creative design are provided. A prototype system of car body design is developed to testify the effectiveness of the proposed method.

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