Image de couverture de livre

The Principle of Proportional Duty: A Knowledge-Duty Framework for Ethical Equilibrium in Human and Artificial Systems

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Prescher, Timothy
Format:	Preprint
Publié:	2025
Sujets:	Artificial Intelligence Optimization and Control
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Joint Planning of Charging Stations and Power Systems for Heavy-Duty Drayage Trucks
par: Ye, Zuzhao, et autres
Publié: (2024)

Energy Management for Renewable-Colocated Artificial Intelligence Data Centers
par: Li, Siying, et autres
Publié: (2025)

The Mathematics of Artificial Intelligence
par: Peyré, Gabriel
Publié: (2025)

Distributionally Robust Free Energy Principle for Decision-Making
par: Shafiei, Allahkaram, et autres
Publié: (2025)

Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process
par: Fan, Zhenan, et autres
Publié: (2024)

A General Equilibrium Theory of Orchestrated AI Agent Systems
par: Garnier, Jean-Philippe
Publié: (2026)

A Discrete-Time Switching System Analysis of Q-learning
par: Lee, Donghwan, et autres
Publié: (2021)

Human-in-the-Loop AI for HVAC Management Enhancing Comfort and Energy Efficiency
par: Liang, Xinyu, et autres
Publié: (2025)

Model Predictive Control and Reinforcement Learning: A Unified Framework Based on Dynamic Programming
par: Bertsekas, Dimitri P.
Publié: (2024)

A Clustering-Based Variable Ordering Framework for Relaxed Decision Diagrams for Maximum Weighted Independent Set Problem
par: Nafar, Mohsen, et autres
Publié: (2025)

Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems
par: Liu, Jiaxin, et autres
Publié: (2026)

Solving Functional Optimization with Deep Networks and Variational Principles
par: Kamtue, Kawisorn, et autres
Publié: (2024)

Intelligent Duty Cycling Management and Wake-up for Energy Harvesting IoT Networks with Correlated Activity
par: Ruíz-Guirola, David E., et autres
Publié: (2024)

Congestion Reduction in EV Charger Placement Using Traffic Equilibrium Models
par: Kara, Semih, et autres
Publié: (2025)

ResearchEVO: An End-to-End Framework for Automated Scientific Discovery and Documentation
par: Zhao, Zhe, et autres
Publié: (2026)

Toward Decision-Oriented Prognostics: An Integrated Estimate-Optimize Framework for Predictive Maintenance
par: Xie, Zhuojun, et autres
Publié: (2025)

System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility
par: Saves, Paul, et autres
Publié: (2025)

A Context-Free Smart Grid Model Using Complex System Approach
par: Amor, Soufian Ben, et autres
Publié: (2025)

IoT-based Fresh Produce Supply Chain Under Uncertainty: An Adaptive Optimization Framework
par: Seth, Chirag, et autres
Publié: (2025)

Temporal Robustness in Discrete Time Linear Dynamical Systems
par: Metya, Nilava, et autres
Publié: (2025)

The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training
par: Wang, Jinbo, et autres
Publié: (2025)

Feasible Pairings for Decentralized Integral Controllability of Non-Square Systems
par: Tong, Yuhao, et autres
Publié: (2026)

Large-scale Online Ridesharing: The Effect of Assignment Optimality on System Performance
par: Fiedler, David, et autres
Publié: (2023)

A Method to Improve the Performance of Reinforcement Learning Based on the Y Operator for a Class of Stochastic Differential Equation-Based Child-Mother Systems
par: Yin, Cheng, et autres
Publié: (2023)

Approximate Information States for Worst-Case Control and Learning in Uncertain Systems
par: Dave, Aditya, et autres
Publié: (2023)

From MIDI to Rich Tablatures: an Automatic Generative System incorporating Lead Guitarists' Fingering and Stylistic choices
par: Bontempi, Pierluigi, et autres
Publié: (2024)

Unifying Controller Design for Stabilizing Nonlinear Systems with Norm-Bounded Control Inputs
par: Li, Ming, et autres
Publié: (2024)

Deep Reinforcement Learning Optimization for Uncertain Nonlinear Systems via Event-Triggered Robust Adaptive Dynamic Programming
par: Bai, Ningwei, et autres
Publié: (2025)

Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers
par: Lau, Tim Tsz-Kit, et autres
Publié: (2026)

Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities
par: Khatim, Nur Ahmad, et autres
Publié: (2026)

A Minimalist Bayesian Framework for Stochastic Optimization
par: Wang, Kaizheng
Publié: (2025)

Knowledge Transfer based Evolutionary Deep Neural Network for Intelligent Fault Diagnosis
par: Sharma, Arun K., et autres
Publié: (2021)

Evolving Scientific Discovery by Unifying Data and Background Knowledge with AI Hilbert
par: Cory-Wright, Ryan, et autres
Publié: (2023)

Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months
par: Rezk, Fady, et autres
Publié: (2023)

Mission-Aligned Learning-Informed Control of Autonomous Systems: Formulation and Foundations
par: Kungurtsev, Vyacheslav, et autres
Publié: (2025)

A Unified Framework for Gradient Aggregation in Multi-Objective Optimization
par: Hu, Zeou, et autres
Publié: (2026)

BenLOC: A Benchmark for Learning to Configure MIP Optimizers
par: Li, Hongpei, et autres
Publié: (2025)

CAM-Bench: A Benchmark for Computational and Applied Mathematics in Lean
par: Long, Wentao, et autres
Publié: (2026)

Offline Supervised Learning V.S. Online Direct Policy Optimization: A Comparative Study and A Unified Training Paradigm for Neural Network-Based Optimal Feedback Control
par: Zhao, Yue, et autres
Publié: (2022)

Learning for routing: A guided review of recent developments and future directions
par: Zhou, Fangting, et autres
Publié: (2025)