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检索条件"任意字段=15th Conference on Behavior Representation in Modeling and Simulation 2006"

共 207 条记录，以下是1-10 订阅

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Imitation Learning for Social simulation 15th

Imitation Learning for Social Simulation

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15th International conference on Social Computing, behavioral- Cultural modeling and Prediction (SBP) / behavior representation in modeling and simulation conference (BRiMS)

作者： Downes, Justin Kavak, Hamdi George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9783031171147;9783031171130

modeling the behavior of complex agents is challenging. In social systems, agents have different motivating factors and goals that drive each decision. In some situations, though, we can observe the agent behavior and the outcomes while being at a loss on how to quantify the decision-making process. Imitation learning is a powerful tool to learn behavior without understanding reasoning. In this paper, we explore modern machine learning techniques to train models that imitate agents' behavior in social environments. this work continues and builds off of emerging work that merges social simulation and modern machine learning. We have shown that such surrogate models can learn heuristicallydriven agent behavior. We note that, however, these models do show fragility to changes in environmental dynamics.

关键词： Agent-based modeling Imitation learning Computer vision Social science Surrogate models Direct policy learning

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OSIRIS: Organization simulation in Response to Intrusion Strategies 15th

OSIRIS: Organization Simulation in Response to Intrusion Str...

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15th International conference on Social Computing, behavioral- Cultural modeling and Prediction (SBP) / behavior representation in modeling and simulation conference (BRiMS)

作者： Shin, Jeongkeun Dobson, Geoffrey B. Carley, Kathleen M. Carley, L. Richard Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9783031171147;9783031171130

OSIRIS, Organization simulation In Response to Intrusion Strategies, is an agent-based simulation framework that models virtual organization composed of end user agents with complex and realistic behavior patterns. the purpose of OSIRIS is to predict and analyze the scale of cyberattack damage on the organization once targeted by cybercriminals with a consideration of organization members' properties, behavior patterns, and social relations. In this paper, we detail how we reflect real world organization environments and cyberattack scenarios to OSIRIS by illustrating our organization and cybercriminal design.

关键词： Agent-based modeling and simulation Human behavior modeling Organization studies

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modeling electron acceleration during the contraction of a magnetic island 15

Modeling electron acceleration during the contraction of a m...

引用

15th International conference on Numerical modeling of Space Plasma Flows (ASTRONUM)

作者： Deuja, Atit Che, Haihong Univ Alabama Huntsville Ctr Space Plasma & Aeron Res CSPAR Huntsville AL 35899 USA Univ Alabama Huntsville Dept Space Sci Huntsville AL 35899 USA

Magnetic reconnection releases the magnetic energy through the contraction of multi-magnetic island leading to the electron acceleration as proposed by Drake et. al in 2006. However, how the released magnetic energy is converted into electron's kinetic energy is still theoretically not well understood. We model in particular the kinetic process assuming the adiabatic contraction of magnetic island that induces electric field which is proportional to the vector potential of the magnetic island and approximate the magnetic island with an ellipse. Under this model, we show that the energy gain is achieved through the work of inductive electric field. We further show that the curvature drift which is along the inductive electric field dominates the energy gain. We compared our model with the magnetic island formed by tearing instability in a 2.5D particle-in-cell simulation of magnetic reconnection and found the results from the model consistent with that of the simulation.

关键词： Electric fields

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Computational Models for Social Good: Beyond Bias and representation 15th

Computational Models for Social Good: Beyond Bias and Repres...

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15th International conference on Social Computing, behavioral- Cultural modeling and Prediction (SBP) / behavior representation in modeling and simulation conference (BRiMS)

作者： Dancy, Christopher L. Joseph, Kenneth Penn State Univ University Pk PA 16802 USA Univ Buffalo Buffalo NY 14260 USA

ISBN: (纸本)9783031171147;9783031171130

this panel will bring a timely and overdue discussion to SBP-BRiMS on computational social and behavioral modeling for social good. What's more, we will host a discussion on what it means to critically approach social good in a way that moves beyond discussions of bias and representation. During this panel, panelists will introduce themselves and positions on topics related to social good within computational behavioral and social modeling, and (along with audience members) proceed to discuss sub-topics, queries, and provocations. Chris Dancy will moderate the discussion and ensure an opportunity for interactive experience for all of those in attendance.

关键词： Computational social good behavioral modeling Social modeling Systems of oppression Critical imagination

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POLARIS-LC: A Multi-Class traffic Flow Model in Lagrangian Coordinates for Large-Scale simulation 15

POLARIS-LC: A Multi-Class traffic Flow Model in Lagrangian C...

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15th International conference on Ambient Systems, Networks and Technologies Networks, ANT 2024 / the 7th International conference on Emerging Data and Industry 4.0, EDI40 2024

作者： De Souza, Felipe Gurumurthy, Krishna Murthy Verbas, Omer Auld, Joshua Transportation and Power Systems Division Argonne National Laboratory 9700 S Cass Ave LemontIL United States

Agent-based modeling has become increasingly prevalent in transportation systems simulation as the scenarios around new technologies and policies become increasingly complex. this increased complexity, in terms of traveler behavior, traffic flow, modal operations, system management, and so on, requires increasingly sensitive and detailed representation of the core components of the simulation, especially as it relates to traffic flow. Many future mobility solutions rely on connectivity, communication, advanced sensing, and detailed information flows, while the simulation also needs to remain computationally tractable. In this paper, we propose a new Lagrangian Coordinate within the POLARIS Agent-Based-modeling Framework (LC-POLARIS) of traffic flow, which combines computational efficiency while adding microscopic features. this model allows multi-class traffic flow by setting different speed-spacing relationships. In this modeling, automated vehicles have lower reaction time, while light-duty trucks have lower free-flow speed and higher jam spacing. the model captures the reduction in capacity and higher queue spillback because of higher jam spacing of trucks. Also, the model yields higher capacity for both passenger and light duty automated vehicles on expressways. the LC-ABM traffic flow model is validated in Bloomington, IL, USA, in a scenario with different rates of four vehicle types. © 2024 Argonne National Laboratory.

关键词： Trucks

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Classifying COVID-19 Related Meta Ads Using Discourse representation through a Hypergraph 15th

Classifying COVID-19 Related Meta Ads Using Discourse Repres...

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15th International conference on Social Computing, behavioral- Cultural modeling and Prediction (SBP) / behavior representation in modeling and simulation conference (BRiMS)

作者： Jeong, Ujun Alghamdi, Zeyad Ding, Kaize Cheng, Lu Li, Baoxin Liu, Huan Arizona State Univ Tempe AZ 85281 USA Univ Illinois Chicago IL USA

ISBN: (纸本)9783031171147;9783031171130

Despite Meta's efforts to promote health information in the COVID-19 pandemic, the growing number of ads is making online content control extremely challenging. To effectively categorize the ads, this work investigates the major discourses shared across Meta ads with various categories related to COVID-19. We propose an interpretable classification model that captures common discourses in the form of keywords and phrases in ads. Particularly, we propose to use hypergraph to connect ads and discourses to capture their high-order interactions. Experiments on a curated Meta Ads dataset show that our model can provide subject-specific discourses and improve classification performance significantly.

关键词： Meta advertisement Text classification Hypergraph

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15th International conference on Social Computing, behavioral-Cultural modeling and Prediction and behavior representation in modeling and simulationconference, SBP-BRiMS 2022

15th International Conference on Social Computing, Behaviora...

引用

15th International conference on Social Computing, behavioral-Cultural modeling and Prediction and behavior representation in modeling and simulationconference, SBP-BRiMS 2022

ISBN: (纸本)9783031171130

the proceedings contain 25 papers. the special focus in this conference is on Social Computing, behavioral-Cultural modeling and Prediction and behavior representation in modeling and simulation. the topics include: Competing State and Grassroots Opposition Influence in the 2021 Hong Kong Election;revisiting Linus’ Law in OpenStreetMap: An Agent-Based Approach;OSIRIS: Organization simulation in Response to Intrusion Strategies;detection of Coordination Between State-Linked Actors;counteracting Filter Bubbles with Homophily-Aware Link Recommendations;mutual Information Scoring: Increasing Interpretability in Categorical Clustering Tasks with Applications to Child Welfare Data;imitation Learning for Social simulation;modeling Memory Imprints Induced by Interactions in Social Networks;unleashing Computational Organization theory with Quantum Probability theory;mitigation of Optimized Pharmaceutical Supply Chain Disruptions by Criminal Agents;cultural Value Resonance in Folktales: A Transformer-Based Analysis with the World Value Corpus;transition to Adulthood for Young People with Intellectual or Developmental Disabilities: Emotion Detection and Topic modeling;optimizing Pharmaceutical and Non-pharmaceutical Interventions During Epidemics;automated Utterance Labeling of Conversations Using Natural Language Processing;an Exploratory Study on the Author Keyphrases Selection Behaviours in Scientific Articles;computational Models for Social Good: Beyond Bias and representation;Evolution of Intent and Social Influence Networks and their Significance in Detecting COVID-19 Disinformation Actors on Social Media;Classifying COVID-19 Related Meta Ads Using Discourse representation through a Hypergraph;a Systematic Approach for Contextualizing Focal Structure Analysis in Social Networks;frames and their Affective Dimensions: A Case Study of Climate Change News Articles;how Is Vaping Framed on Online Knowledge Dissemination Platforms?;the Missing Link Between User Engagement and M

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An Intelligent Ranking Evaluation Method of simulation Models Based on Graph Neural Network 15th

An Intelligent Ranking Evaluation Method of Simulation Model...

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15th EAI International conference on simulation Tools and Techniques, SIMUTools 2023

作者： Yang, Fan Ma, Ping Zhang, Jianchao Cheng, Huichuan Li, Wei Yang, Ming Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Modeling and Simulation Harbin150080 China Chinese Aeroengine Research Institute Beijing101304 China

ISBN: (纸本)9783031575228

To validate the alternative simulation models and select the most credible one when the models have multivariate and correlated outputs, an intelligent ranking evaluation method of simulation models based on Graph Neural Network (GNN) is proposed. the process of ranking evaluation is divided into three parts: graph structure conversion for evaluation data, feature extraction based on Graph representation Learning (GRL) and ranking evaluation based on feature distance. A graph structure modeling method is presented to provide the pre-define graph structure for further GRL primarily. Next the interdependencies and dynamic evolutionary patterns among variables are captured by GNN so that the graph representations of evaluation data can be obtained. then ranking evaluation is achieved by similarity measurement of the graph representations. In the end, the effectiveness of the proposed method on feature extraction of evaluation data and simulation models ranking is illustrated through an application example on a prediction model for aerodynamic parameters of a certain flight vehicle. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Feature extraction

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Transition to Adulthood for Young People with Intellectual or Developmental Disabilities: Emotion Detection and Topic modeling 15th

Transition to Adulthood for Young People with Intellectual o...

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15th International conference on Social Computing, behavioral- Cultural modeling and Prediction (SBP) / behavior representation in modeling and simulation conference (BRiMS)

作者： Liu, Yan Laricheva, Maria Zhang, Chiyu Boutet, Patrick Chen, Guanyu Tracey, Terence Carenini, Giuseppe Young, Richard Carleton Univ Ottawa ON Canada Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9783031171147;9783031171130

Transition to Adulthood is an essential life stage for many families. the prior research has shown that young people with intellectual or development disabilities (IDD) have more challenges than their peers. this study is to explore how to use natural language processing (NLP) methods, especially unsupervised machine learning, to assist psychologists to analyze emotions and sentiments and to use topic modeling to identify common issues and challenges that young people with IDD and their families have. Additionally, the results were compared to those obtained from young people without IDD who were in transition to adulthood. the findings showed that NLP methods can be very useful for psychologists to analyze emotions, conduct cross-case analysis, and summarize key topics from conversational data. Our Python code is available at https://***/mlaric heva/emotion_topic_modeling.

关键词： Transition to adulthood Intellectual or development disabilities Emotion detection Sentiment analysis Topic modeling Natural language processing

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Detection of Coordination Between State-Linked Actors 15th

Detection of Coordination Between State-Linked Actors

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15th International conference on Social Computing, behavioral- Cultural modeling and Prediction (SBP) / behavior representation in modeling and simulation conference (BRiMS)

作者： Erhardt, Keeley Pentland, Alex MIT Media Lab Cambridge MA 02139 USA

ISBN: (纸本)9783031171147;9783031171130

Powerful actors have engaged in information control for centuries, restricting, promoting, or influencing the information environment as it suits their evolving agendas. In the Digital Age, information control has moved online, and information operations now target the online platforms that play a critical role in news engagement and civic debate. In this paper, we use a discrete-time stochastic model to analyze coordinated activity in an online social network, representing the behaviors of accounts as interacting Markov chains. From a dataset of 31,521 tweets posted by 206 accounts, half of which were identified by Twitter as participating in a state-linked information operation, we evaluate the coordination, measured by the apparent influence, between pairs of state-linked compared to unaffiliated accounts. We find that the state-linked actors exhibit more coordination amongst themselves than with the unaffiliated accounts. the degree of coordination between the state-linked accounts is also much higher than the observed coordination between the unaffiliated accounts. Additionally, we find that the account that represented the most coordinated activity in the network had no followers, demonstrating the power of our modeling approach to unearth hidden connections even in the absence of explicit network structure.

关键词： Coordinated activity Influence modeling Markov chains

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