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reinforcement learning

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#reinforcement learning Open access Sep 2026

Study record and reproduction code for a survey of evaluation design and disclosure requirements in reinforcement learning-based route guidance

Reproduction material for the survey "Study-Area Boundaries in Reinforcement Learning-Based Route Guidance: A Survey of Evaluation Design and Disclosure Requirements" by Donghoun Lee. The package holds the study record of the 93 reviewed studies, one row per study with the sentence of the research article behind each r...

Donghoun Lee · 0 citations
#reinforcement learning Open access Sep 2026

Implementation of the Discovery Learning Model Assisted by Wordwall Games Media in History Learning

This study examines the planning and implementation of the Discovery Learning model assisted by Wordwall Games media in history learning and identifies the obstacles encountered during its implementation in class XI F1 of SMA Negeri 1 Sungai Rumbai. The study used a descriptive qualitative approach. The research inform...

Yola Yuspita, Kaksim Kaksim, Liza Husnita · 0 citations
#reinforcement learning Book Open access Sep 2026

Exercises in Mathematical Foundations for Reinforcement Learning: A Companion Workbook

Reading a complete mathematical proof and constructing one are different skills. This workbook develops the second through structured practice with the mathematical foundations used in reinforcement learning. The volume contains 93 exercises aligned with Chapters 2–17 of Mathematical Foundations for Reinforcement Learn...

Tenorio Salvador · 0 citations
#reinforcement learning Open access Sep 2026

Can Cooperative Routing Mitigate System-Level Inefficiency in Road Networks?

Traffic congestion in urban road networks represents a fundamental coordination failure, where the aggregate behavior of self-interested agents results in a high “Price of Anarchy” that compromises system-wide efficiency. In decentralized settings, agents typically maximize local utility without accounting for the cong...

Shima Rahmani, Ivana Budinská, Brian Caulfield et al. · 0 citations
#reinforcement learning Open access Sep 2026

AI-Guided Multi-Objective Engineering of Glucoamylase Enables Acidification-Free Starch Saccharification

An artificial intelligence-guided strategy to simultaneously improve the thermostability, pH tolerance, and catalytic activity of glucoamylase from Penicillium oxalicum (PoGA) and folding energy guided recombination to achieve simultaneous multi property optimization is developed.

Jie Qiao, Xiao-Rui Ma, Yi-Bo Song et al. · 0 citations
#reinforcement learning Open access Sep 2026

Convergence and Divergence: Forces Shaping Marmoset Vocal and Social Interactions

Human language hinges on a remarkable capacity for vocal production learning, yet the evolutionary origins of this ability remain poorly understood. This thesis explores the idea that increasing cooperation and social interdependence played a major role in the evolution of vocal flexibility in the hominin lineage. To i...

Nikhil Phaniraj · 0 citations

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Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

MIT News · Artificial Intelligence Oct 7, 2026

Discovering the value of humanistic inquiry

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.

Microsoft Research Blog Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

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.

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