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1,703 papers
The speed of cloud computing and artificial intelligence, which have transformed the way software applications are designed and deployed. The cloud-based AI systems provide a scalable, adaptable, and cost-efficient solution to build intelligent systems capable of processing large amounts of data and running complicated...
Autonomous multi-agent artificial intelligence (AI) systems have emerged as a rapidly evolving field that revolutionizes the way autonomous systems can make decisions together, collaborate on tasks, and learn, thereby opening new paradigms for distributed decision-making, task execution, and adaptive learning. The comp...
The effectiveness of Management Information Systems (MIS) in elementary schools has become an important issue as educational governance increasingly requires efficient, accurate, transparent, and data-based management. This study aims to systematically examine the effectiveness of MIS implementation in elementary schoo...
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The Dark Forest hypothesis is usually presented as a general consequence of uncertainty, technological asymmetry and catastrophic vulnerability. This paper asks a narrower question: under which combinations of beliefs, capabilities, signalling conditions and network incentives does a Dark Forest actually emerge? A Dark...
The Dark Forest hypothesis is usually presented as a general consequence of uncertainty, technological asymmetry and catastrophic vulnerability. This paper asks a narrower question: under which combinations of beliefs, capabilities, signalling conditions and network incentives does a Dark Forest actually emerge? A Dark...
Dark Forest arguments commonly reduce interstellar strategy to a bilateral encounter between two persistent civilisations. A galaxy, however, is an open population in which civilisations enter, disappear, form selective relationships and occupy a spatially constrained network. This paper develops a continuous-time Gala...
Dark Forest arguments commonly reduce interstellar strategy to a bilateral encounter between two persistent civilisations. A galaxy, however, is an open population in which civilisations enter, disappear, form selective relationships and occupy a spatially constrained network. This paper develops a continuous-time Gala...
Reliability Beyond Accuracy in Crop Classification Benchmarks (Supplementary Materials)Introduction: Near-perfect crop-label accuracy can conceal uncertainty, perturbation sensitivity, and weak explanations. This study evaluates these reliability dimensions without treating benchmark classification as agronomic recomme...
Reliability Beyond Accuracy in Crop Classification Benchmarks (Supplementary Materials)Introduction: Near-perfect crop-label accuracy can conceal uncertainty, perturbation sensitivity, and weak explanations. This study evaluates these reliability dimensions without treating benchmark classification as agronomic recomme...
This paper critically examines the foundational assumptions of rational decision-making models and finds them to be systematically and comprehensively flawed. Through a rigorous analysis of empirical evidence from behavioral economics and neuroscience, we demonstrate that traditional models, such as Expected Utility Th...
This paper critically examines the foundational assumptions of rational decision-making models and finds them to be systematically and comprehensively flawed. Through a rigorous analysis of empirical evidence from behavioral economics and neuroscience, we demonstrate that traditional models, such as Expected Utility Th...
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
The effort aims to help U.S. learners from kindergarten to community college, with an emphasis on math, making, and the constructive use of AI.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
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