Artificial Intelligence and Robotics Commons^™

Expert Interview: "The Mirror Of Ai" In The Domain Of Scientifc Information Research, Taitian Mao, Yulai Bao, Jianxiang Wei, Peng Wu, Chuanming Yu, Gan Tang, Dongyan Wei, Yifei Ma, Wei Wang, Yu Ma

Journal of Scientific Information Research

Professor Mao Taitian and colleagues argues elucidates the adaptation logic, practical pathways, and prerequisites of intelligent agents to empower the high-quality development of scientific information. Professor Bao Yulai and colleagues advocate that integrating the perceptual elasticity of domain-specific large models with the cognitive rigidity of ontology can establish a new paradigm for intelligence services in complex scenarios. The synergy between the two can not only expand the theoretical boundaries of information science and serve national strategies, but also advance intelligence services from assisted analysis to intelligent decision-making. Professor Wei Jianxiang and colleagues point out that generative artificial intelligence has triggered …

Religious Bias In Llms Is Significantly Understudied, Sheryl Carty, Nancy Fulda, Walter Reade

Faculty Publications

In the earlier years of development of LLMs, it was relatively easy to prompt an LLM to respond with toxic or biased statements about religion. Subsequent improvements in frontier models addressed many of the issues of bias and toxicity in general, including against religion. At the same time, the adoption and usage of these models has grown exponentially. Small and implicit biases, therefore, have a magnified overall impact. In this paper, we (1) briefly review previous efforts to measure religious bias in LLMs, (2) show, by reviewing over 12,000 papers dealing with bias in LLMs, that religious bias has been …

Heterogeneous Graph-Augmented Contrastive Learning For Extreme Multi-Class Fiqh Classification, Ali A. Jalil

Al-Bahir

• Background/Introduction: Fine-grained text classification in the field of Islamic Jurisprudence (Fiqh) is difficult because of the structural interdependence of the legal concepts and the extremely multi-class long-tail data distribution (667 classes with 5,979 samples, 52.2% of which contain less than 5 samples). The main problem with traditional flat classifiers is that they assume that target classes are independent and orthogonal output neurons which discards very important relational semantics.
• Objectives: This paper seeks to remediate this extreme imbalance and maintain structural taxonomy by modeling the structural space of classification label space itself as an object to be learned, while giving a …

Chi Meta-Project Ecosystem Overview - Spring 2026, David B. Smith

Publications and Research

This paper offers a high-level account of the Center for Holistic Integration’s (CHI) meta-project ecosystem as visualized in the included system map. CHI provides an organizational structure framed around persistent meta-projects that support and extend individual initiatives across curriculum, scholarly and applied research, infrastructure, artistic production, AI development, cultural inquiry, and external partnerships. Rather than presenting the map as a static inventory of projects, the paper examines how its core domains function as living systems through which knowledge, tools, documentation, participants, and collaborations can accumulate over time. It also considers how CHI-mediated connectivity, institutional integration, and external funding allow the …

A Machine-Learning-Based Systematic Framework For Modeling Compression And Recompression Indices For Florida Soils, Michael Morales

Doctoral Dissertations and Master's Theses

This thesis develops a machine-learning framework for estimating the compression index and the recompression index of Florida soils from routinely measured index properties, and reports two studies that build it. Consolidation settlement design requires both indices, and both are obtained from the incremental-loading oedometer test, which occupies a specimen for one to two weeks; the index tests that accompany it are complete within hours. Empirical correlations have filled that interval since the 1950s, but their coefficients are calibrated on specific soil populations and transfer poorly between regions. The first study analyzes 376 consolidation tests compiled for the Florida Department of …

Online Ppo-Based Multi-Hop Task Offloading Strategy For Vehicular Edge Computing, Wenzhu Zhang, Yuewei Bian, Fuli Xiong, Siqi Cai

Journal of System Simulation

Abstract: To address the problems of frequent communication link interruptions caused by dynamic network topologies and the sharp increase in computational complexity triggered by high-dimensional decision spaces in the vehicular edge computing (VEC) environment, a multi-hop task offloading strategy for VEC based on an online PPO algorithm was proposed. A multi-hop task offloading optimization model simultaneously considering link effective time, transmission rate, and computing resource constraints was constructed; a multi-hop A* path search algorithm integrating link stability and end-to-end delay was designed; an online offloading decision framework based on PPO was proposed, which transformed the 0-1 mixed integer nonlinear programming …

Research On Temporal Action Localization Methods For Cross-Modal Understanding, Jinwei Li, Xiaoyang Liu, Rusheng Ju

Journal of System Simulation

Abstract: To address the problems of insufficient localization accuracy and high model complexity in the temporal action localization (TAL) task for video-text cross-modal understanding, an anchor-free action transformer (AFAT) model was proposed. Based on the anchor-free framework, the local self-attention mechanism of Transformer was introduced to enhance the global modeling capability of temporal features. A multi-scale feature pyramid structure was combined to strengthen the representation of actions with different durations, and a lightweight predictor was adopted to reduce computational redundancy. Experimental results show that the average precision of this model on the THUMOS14 dataset is significantly improved compared with the …

There Is No Free Benchmark: An Institutional View Of Legal Ai Benchmarking, Neel Guha, Andy K. Zhang, Christine Tsang, Christopher D. Manning, Julian Nyarko, Daniel E. Ho

Faculty Scholarship

Despite substantial excitement around the use of AI in law, little information exists on the performance and associated risks of the domain’s widely marketed tools. Recent work, for instance, has demonstrated the significant potential for “hallucinations” — wherein models make up facts, law, and precedent — leading Chief Justice Roberts to spotlight this risk in his annual report on the judiciary. We argue that there is a need for public AI benchmarking in law. First, relative to other AI application domains, the legal AI ecosystem lacks legibility — there is little information about the design and performance of many commercial …

Semantic Context Improvisational Retrieval-Augmented Generation For Empathic Conversational Ai, Sharjeel Tahir, Judith Johnson, Jumana Abu-Khalaf, Syed Afaq Ali Shah

Research outputs 2022 to 2026

A fundamental limitation of modern conversational AI is its limited capacity to demonstrate sustained empathy in long-form interactions. We propose SCIRAG (Semantic Context Improvisational Retrieval-Augmented Generation), a feedback-driven retrieval framework for adaptive empathic dialogue. It employs a dual-loop retrieval framework, iteratively optimizing a static counseling dataset through user metadata and feedback memory refinement. To enhance contextual alignment, we deploy retrieval adaptation, enabling the model to retain and leverage past conversational cues based on user preferences. When integrated with Mixtral-8x7B, SCIRAG improves human-rated empathic understanding by +1.26 points and empathic response by +1.00 point on the RoPE scale, while increasing acceptability …

Resilience Modeling Method For Combat System-Of-Systems Based On Hypernetwork And Game Theory, Yuxian Duan, Hanqiang Deng, Jiarui Zhang, Jian Huang, Shijia Zhang

Journal of System Simulation

Abstract: In view of the difficulties in dynamic reconfiguration and resilience evaluation faced by modern combat system-of-systems in a highly adversarial environment, and the deficiencies of existing studies in depicting high-order interaction relationships and cluster evolution mechanisms, this paper proposed a resilience modeling method for combat system-of-systems integrating hypernetwork and game theory, aiming to analyze the resilience mechanism of the system-of-systems in all dimensions from micro, mesoscopic, to macro levels. At the micro level, a high-order motif structure was introduced to represent the complex interaction modes among combat units, which overcame the information loss of traditional binary relationships in depicting …

Simulation Study Of Elevator Group Control Scheduling Based On Real-Time Occupancy Perception, Yiyong Han, Shiyu Wang, Yang Ye, Zhen Zhang, Fengque Pei, Minghai Yuan

Journal of System Simulation

Abstract: To address the conflict between car space allocation and peak passenger flow response efficiency in elevator group control scheduling, a multi-objective scheduling method based on proximal policy optimization (PPO) with real-time occupancy perception was proposed. A simulation environment considering car capacity constraints was constructed, and a reward-penalty mechanism with average passenger waiting time, system energy consumption, and car congestion as optimization objectives was designed. Based on this, state and action spaces were defined to form a PPO-based scheduling framework; a simulation platform integrating traffic flow visualization, policy scheduling, and performance evaluation was developed. Simulation results show that this method …

Adaptive Spatiotemporal Graph Neural Network-Based Net Load Forecasting For Residential Areas, Yongqi Yang, Cong Wang, Hongli Zhang, Ping Ma, Yue Meng, Tianhao Zhou

Journal of System Simulation

Abstract: To address the issue that traditional residential overall power load forecasting methods fail to fully consider the differences in users' electricity consumption habits, making it difficult to improve prediction accuracy, a residential net load forecasting method combining representation learning clustering and an AGCN-Transformer was proposed. The representation learning method was utilized to fully extract the latent features of users' net load data, and users were divided into different groups based on the similarity of electricity consumption behaviors; the net load data of the same group were aggregated, and a graph structure suitable for this task was constructed by comprehensively …

Evolution And Prospects Of Polarization Image Simulation Technology, Gengpeng Li, Wei Cai, Zhiyong Yang, Zhili Zhang, Xiaowei Wang

Journal of System Simulation

Abstract: Polarization image simulation technology is a key means to break through the bottleneck of polarization data acquisition and promote the development of polarization vision. This study systematically reviewed three evolutionary paradigms of this technology: Physical mechanism simulation, based on the polarization bidirectional reflectance distribution function and polarization ray tracing, strictly solves polarization light transmission, which has high interpretability and credibility, but it is computationally complex and lacks visual realism. Data-driven simulation, using models like neural radiance fields to learn polarization appearance from data, has high generation efficiency and visual fidelity but weaker physical consistency and interpretability. Physics-data fusion simulation …

Mbse Design And Approach-Phase Operational Simulation Of Bdsbas Airborne Receiver, Ruihua Liu, Tongwei Wang, Zan Ma

Journal of System Simulation

Abstract: In view of the problem that traditional document-based design methods are difficult to effectively capture the dynamic characteristics and internal interactions in navigation accuracy and integrity assurance required by BeiDou satellite-based augmentation system (BDSBAS) airborne receivers during the approach phase, which easily leads to designs deviating from actual requirements and affects system performance, a model-based systems engineering(MBSE) method was introduced. A multi-dimensional system architecture model encompassing system requirement analysis, behavior description, structure design, and parameter constraints was established. Taking BDSBAS as the object, a co-simulation method of system modeling language and MATLAB for required navigation performance (RNP) was proposed, …

Simulation Study On The Vulnerability Of Belt And Road Composite Transportation Network Based On Cascading Failure, Mingjun Qian, Chao Yin, Zhiwen Huang, Quanneng Wang

Journal of System Simulation

Abstract: To address the issues of unclear cascading failure propagation mechanisms and difficult-to-quantify vulnerability evolution laws caused by the structural complexity and node heterogeneity of the "Belt and Road" multimodal transport network, a vulnerability assessment method for composite transportation networks integrating physical analogy and improved cascading failure model was proposed. Sub-networks were constructed based on main transportation modes of the Belt and Road, and nodes in the same city were coupled to build a composite transportation network model. An information entropy-Joule's law model was constructed to identify key nodes of the composite network and its subnetworks. A load-capacity cascading failure …

Distributed Cooperative Control Of Swarm Unmanned Aerial Vehicles Based On Multi-Route Clustering, Yuyang Xiong, Chuntao Li, Wenhao Qiu

Journal of System Simulation

Abstract: To address the collaborative control and formation maintenance problems of large-scale swarm unmanned aerial vehicles, a distributed cooperative control method for unmanned aerial vehicles based on multi-route clustering was proposed. Leveraging the characteristics of multiple routes, the overall cooperative control problem of the swarm was decoupled into the cooperative control within the same route and the consensus control between multiple routes. Within the same route, a forward-neighbor information interaction mechanism was designed to determine the neighbor relationships, and a velocity-guided cooperative algorithm was utilized to achieve the desired velocity matching and spacing maintenance of unmanned aerial vehicles; between multiple …

Multi-Scale Modeling Method For Intelligent Unmanned Aerial Vehicle Swarm Combat, Yelei Zhu, Shoulin Shen, Jiang Zhu, Chuanhua Wen

Journal of System Simulation

Abstract: Intelligent unmanned aerial vehicle swarm combat exhibits multi-scale characteristics of microlevel tactical autonomy, meso-level resource constraints, and macro-level network collaboration. In view of the problem that a single-scale modeling method is difficult to simultaneously characterize individual decision-making details, resource flow process, and system collaboration mechanism, a multi-scale modeling method integrating multi-agent modeling, system dynamics, and complex network theory was proposed. By designing six formal coupling operators to achieve cross-layer information mapping, a time progression mechanism based on a master-slave clock and hybrid synchronization was established, and a proof of error boundedness was provided. A prototype system was implemented on …

Modeling And Simulation Of Efficient State Information Diffusion In Wireless Ad Hoc Networks, Mengyao Jia, Shaozhu Gu, Junhan Wang, Denghao Wang, Du Xu, Xiaoning Zhang

Journal of System Simulation

Abstract: To solve the problems of significant communication overhead and limited real-time response capability in the traditional flooding-based state diffusion mechanism, an efficient diffusion algorithm based on regional partitioning and information compression was proposed. A multi-dimensional feature clustering method integrating geographic distance and link quality was used to achieve high-cohesion network partitioning through weighted Euclidean distance and the K-means algorithm; a dynamic selection mechanism for representative nodes was designed to conduct comprehensive scoring by combining the link quality and geographic centrality of nodes, realizing the efficient compression and aggregated transmission of regional information. Simulation results indicate that the algorithm significantly …

Research On Safety Monitoring System For Digital Twin Fully Mechanized Mining Face In Thin Coal Seams, Ya Liu, Zhaoyun Zhang, Cheng An, Canguang Zheng

Journal of System Simulation

Abstract: To solve the problems of opaque production processes, difficult expression of production information, and high difficulty in real-time model driving and safety monitoring in fully mechanized mining faces of thin coal seams, studying the use of digital twin technology and risk early warning models to solve beyond-visual-range visual production operations and safety monitoring control of the working face has important theoretical and practical value. This paper studied the construction methods of the digital twin system for fully mechanized mining faces in thin coal seams and discussed the construction of high-precision three-dimensional models, the real-time collection and processing conversion of …

Trajectory-Aware Dynamic Offloading For High-Mobility Vehicular Edge Systems, Haoran Xu, Zhiqin Huang, Youwu Hu, Zheyi Chen

Journal of System Simulation

Abstract: To address the problems of service interruptions, task failures, and resource waste caused by high mobility of intelligent vehicles (IVs) in vehicular edge computing (VEC), this paper proposes a trajectory-aware dynamic offloading (TADO) framework for high-mobility vehicular edge systems. A lightweight T-pattern trajectory-aware algorithm is designed to efficiently predict the next-hop road side unit (RSU) by mining spatio-temporal patterns from historical trajectories of vehicles, offering a forward-looking reference for offloading decisions. A joint optimization model is constructed, and a service interruption risk factor driven by trajectory prediction is introduced. An improved DRL method is developed. It takes the predicted …