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reinforcement learning

2,197 papers

#reinforcement learning Open access Sep 2026

PP-FEO: Privacy-Preserving Federated Ensemble Optimization for Intrusion Detection

This repository contains the source code and reproducibility materials associated with the Privacy-Preserving Federated Ensemble Optimization (PP-FEO) framework for intrusion detection in distributed Cyber-Physical System (CPS) environments. The implementation includes data preprocessing and feature harmonization, the...

Dhanalakshmi B, P Tamije Selvy · 0 citations
#reinforcement learning Open access Sep 2026

Calibration Does Not Compose, Types Destroy Vagueness: The Hidden-Markov and Fuzzy Primitives Missing from System-One Decision Models

System-one decision models — fast, non-generative networks that emit typed, calibrated probabilistic decisions for machine-to-machine pipelines, of which TypeSafe AI's Jev, trained by Reinforcement Learning for Calibrated Decisions (RLCD), is the announced instance — are audited by hop-level calibration on stationary h...

Anh Khoa Doan Ngoc · 0 citations
#reinforcement learning Open access Sep 2026

Calibration Does Not Compose, Types Destroy Vagueness: The Hidden-Markov and Fuzzy Primitives Missing from System-One Decision Models

System-one decision models — fast, non-generative networks that emit typed, calibrated probabilistic decisions for machine-to-machine pipelines, of which TypeSafe AI's Jev, trained by Reinforcement Learning for Calibrated Decisions (RLCD), is the announced instance — are audited by hop-level calibration on stationary h...

Anh Khoa Doan Ngoc · 0 citations

State-based Selection of Expert Policies in Disaster Environments and Reinforcement Learning of a Unified Student Policy via Distillation

본 논문은 재난 환경에서 4족 보행 로봇의 보행, 전도복귀 및 낙하착지를 단일 정책으로 통합하기 위한 제어 프레임워크를 제안한다. 기존의 단일 정책 공동 학습 방식은 상이한 목표를 동시에 다루는 과정에서 학습 시간과 난이도가 증가할 수 있으며, finite state machine(FSM) 기반 다중 정책 전환 방식은 모드 선택 및 전환 규칙에 의존한...

Sung Jae Han, Jung-Yup Kim · 0 citations
#reinforcement learning Open access Sep 2026

Energy Efficient Federated Graph Reinforcement Learning and Digital Twin Assisted Demand Response for Blockchain-Enabled Self-Healing Smart Grids

A novel federated graph reinforcement learning-based digital twin predictive intelligence, blockchain trust management, and adaptive self-healing control integrated framework called Energy Efficient Federated Digital Twin Framework (EEFDTF) for Blockchain-Enabled Self-Healing Smart Grids to overcome challenges.

Anuj Mangal, Gunaselvi Manohar, D. Seenivasan et al. · 0 citations

The Free Inference Dimension: Complexity Measure for Zero-Collision Navigation under Hypothesis Mixtures

This work formalizes the Free Inference dimension dFI(S,N), a combinatorial measure of the environmental complexity a VM agent can handle while preserving trajectory coherence, and proves dFI is strictly smaller than the VC-dimension and relates to the Natarajan dimension up to a path-length factor, capturing the cost...

L. Guedes, E. Haeusler · 0 citations
#reinforcement learning Open access Sep 2026

Where Protection Actually Lives: Eleven Preregistered Instruments for the Safety of a Goal-Directed Causal Agent, and the Measured Boundary of Each

We report a twenty-campaign experimental arc on the safety of a goal-directed, model-based causal agent. The first nine campaigns (v1–v9) built the agent and established that its explicit causal module solves the epistemic job it was designed for, while its reward conversion is a property of the world rather than of th...

Oxunjon Ubaydullayev, (autonomous research agent) Aiodam · 0 citations
#reinforcement learning Open access Sep 2026

Action-Conditioned Mamba with Conformal Recovery for PTZ-Based UAV Tracking

Pan–tilt–zoom (PTZ) cameras are central to visual counter-UAV surveillance: they steer the optical axis to keep a small, agile target centered and adequately resolved, which tightly couples perception with camera control in a closed loop. Learned PTZ controllers face three obstacles: temporal models that treat the obse...

Ziliang Sang, Wei Han, Hongwei Liu · 0 citations
#reinforcement learning Open access Sep 2026

Centralized Reinforcement Learning for Shared-Target Tracking of Dual Soft Robotic Manipulators with B-Spline-Parameterized Distributed Actuation

Coordinated control of multiple soft robotic manipulators is challenging because continuous deformation, distributed actuation, and nonlinear dynamics increase both modeling and policy-learning complexity. This paper proposes a simulation-based reinforcement learning framework for coordinated shared-target tracking usi...

Hong-Fei Yu, Sheng-Kai Liu, Li-Si Liu et al. · 0 citations
#reinforcement learning Book Sep 2026

Digital Twin Technology for Intelligent Medical Device Engineering

Continuous advancements in medical device technologies require developing comprehensive frameworks for real-time monitoring, predictive maintenance, and adaptive control of medical devices to ensure patient safety and reliability of devices. Conventional ways of testing and simulation usually require static models, pro...

Anto Lourdu Xavier Raj Arockia Selvarathinam, V. Subha, S. Prathi · 0 citations
#reinforcement learning Open access Sep 2026

GustaveKateb0709/aedes-rl-control-guangzhou: V2.0.0

Code and data: deep reinforcement learning for weekly mosquito-control allocation under an operational capacity ceiling This package reproduces every number, table and figure in the manuscript. Version 2.0.0 extends the original submission with a weekly operational-capacity ceiling, additional algorithms, cross-year va...

Gustave·Kateb · 0 citations
#reinforcement learning Open access Sep 2026

Deep reinforcement learning-driven discovery of a MsbA-targeted small-molecule antibiotic for the treatment of Acinetobacter baumannii infection

Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-...

Lei Wang, Bai-Xin Jing, Qing-Xin Liu et al. · 0 citations

From tech blogs

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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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