scholarly journals Working Towards a BDI‑Agent Based on Personality Traits to Improve Normative Conflicts Solution

2017 ◽  
Author(s):  
Paulo H. C. Alves ◽  
Marx L. Viana ◽  
Carlos J. P. De Lucena
Keyword(s):  
Personality Traits ◽  
Agent Based ◽  
Bdi Agent ◽  
Normative Conflicts

scholarly journals Emergent Robotic Personality Traits via Agent-Based Simulation of Abstract Social Environments

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 103
Author(s):  
Casey C. Bennett
Keyword(s):  
Personality Traits ◽  
Human Robot Interaction ◽  
Social Environments ◽  
Agent Based Simulation ◽  
Theoretical Frameworks ◽  
Behavioral Learning ◽  
Agent Based ◽  
Current State ◽  
The Stability ◽  
Markovian Approach

This paper discusses the creation of an agent-based simulation model for interactive robotic faces, built based on data from physical human–robot interaction experiments, to explore hypotheses around how we might create emergent robotic personality traits, rather than pre-scripted ones based on programmatic rules. If an agent/robot can visually attend and behaviorally respond to social cues in its environment, and that environment varies, then idiosyncratic behavior that forms the basis of what we call a “personality” should theoretically be emergent. Here, we evaluate the stability of behavioral learning convergence in such social environments to test this idea. We conduct over 2000 separate simulations of an agent-based model in scaled-down, abstracted forms of the environment, each one representing an “experiment”, to see how different parameters interact to affect this process. Our findings suggest that there may be systematic dynamics in the learning patterns of an agent/robot in social environments, as well as significant interaction effects between the environmental setup and agent perceptual model. Furthermore, learning from deltas (Markovian approach) was more effective than only considering the current state space. We discuss the implications for HRI research, the design of interactive robotic faces, and the development of more robust theoretical frameworks of social interaction.

Exploring Agent-Based Modeling for Emergency Logistics Collaborative Decision Making

2013 ◽  
Vol 710 ◽  
pp. 781-785 ◽  
Author(s):  
Li Zhang ◽  
Zhi Qi ◽  
Hao Cui ◽  
Sen Hua Wang ◽  
Ya Hui Ning ◽  
...  
Keyword(s):  
Decision Making ◽  
Local Level ◽  
Collaborative Decision Making ◽  
Agent Based ◽  
Concept Model ◽  
Emergency Logistics ◽  
Bdi Agent ◽  
Distribution Process ◽  
Multi Agent ◽  
Collaborative Decision

Aiming at the requirements of urgency and dynamics in emergency logistics, this paper presents a multi-agent system (MAS) concept model for emergency logistics collaborative decision making. The suggested model includes three kinds of agents, i.e., role agent, function agent and assistant agent. Role agent excutes emergency logistics activities, function agent achieves the task requirements in every work phase and assistant agent helps organizing and visiting data. Two levels agent views serve as the basic skeleton of the MAS. Top level is the global decision-making view, which describes the task distribution process with multiple agents. Local level is the execution planning view, which simulates task executing process of the performer. Finally, an extended BDI agent structure model is proposed to help the implementation at application level.

scholarly journals DESIGNING A BDI AGENT REACTANT MODEL OF BEHAVIOURAL CHANGE INTERVENTION

2015 ◽  
Vol 78 (2-2) ◽  
Author(s):  
Ojeniyi Adegoke ◽  
Azizi Ab Aziz ◽  
Yuhanis Yusof
Keyword(s):  
Behavioural Change ◽  
Psychological Reactance ◽  
Main Determinant ◽  
Agent Based ◽  
Agent Model ◽  
Design And Implementation ◽  
Psychological Theories ◽  
Bdi Agent ◽  
Behavioural Factors ◽  
Generic Representation

Belief-Desire-Intention (BDI) model is well suited for describing agent’s mental state. The BDI of an agent represents its motivational stance and are the main determinant of agent’s actions. Therefore, explicit understanding of the representation and modelling of such motivational stance plays a central role in designing BDI agent with successful behavioural change interventions. Nevertheless, existing BDI agent models do not represent agent’s behavioural factors explicitly. This leads to a gap between design and implementation where psychological reactance has being identified as the cause of BDI agent behavioural change interventions failure. Hence, this paper presents a generic representation of BDI agent model based on behavioural change and psychological theories. Also, using mathematical analysis the model was evaluated. The objective of the proposed BDI agent model is to bridge the gap between agent design and implementation for successful agent-based interventions. The model will be realized in an agent-based application that motivates children towards oral hygiene. The study explicitly depicts how agent’s behavioural factors interact to enhance behaviour change which will assist agent-based intervention designers to be able to design intervention that will be void of reactance.

scholarly journals Intelligent video interview agent used to predict communication skill and perceived personality traits

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hung-Yue Suen ◽  
Kuo-En Hung ◽  
Chien-Liang Lin
Keyword(s):  
Personality Traits ◽  
Interpersonal Communication ◽  
Communication Skills ◽  
Affective Computing ◽  
Ground Truth ◽  
Critical Issue ◽  
Agent Based ◽  
Initial Stage ◽  
Employment Screening ◽  
Video Interview

AbstractThe prediction of individual interpersonal communication skills and personality traits is a critical issue in both industrial and organizational psychology and affective computing. In this study, we invited 114 participants, including 57 interviewers and 57 interviewees, to collect the ground truth of interviewees’ communication skills and personality traits as perceived by real human interviewers in a structured behavioral interview setting. We develop an asynchronous video interview (AVI) platform with an artificial intelligence (AI) decision agent based on a TensorFlow convolutional neural network (CNN), called AVI-AI, that can be used to partially displace human raters’ work in the initial stage of employment screening and to successfully predict a job candidate’s communication skills and personality traits. The experimental results show that AVI-AI can predict not only a candidate’s interpersonal communication skills but also his or her openness, agreeableness, and neuroticism, as perceived by experienced human resource professionals. The interrater reliability values were all acceptable to support the ground truth assumption. However, our AVI-AI could not predict the conscientiousness and extraversion as perceived by the real human raters in this study.

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