🎮 Reinforcement Learning - chris1 · Scour

FutureWorld: A Live Environment for Training Predictive Agents with Real-World Outcome Rewards 🤖AI Agents

Sample-efficient Neuro-symbolic Proximal Policy Optimization 🧠Neural Networks

Digital Twin-assisted belief-state reinforcement learning for latency-robust ISAC in 6G networks 📐ML Theory

SpecRLBench: A Benchmark for Generalization in Specification-Guided Reinforcement Learning 📐ML Theory

Robust Representation Learning through Explicit Environment Modeling 🤖Machine Learning

From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents 🤖AI Agents

A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication 🤖AI Agents

Reward Models Are Secretly Value Functions: Temporally Coherent Reward Modeling ♟️Game Theory

Safe Navigation using Neural Radiance Fields via Reachable Sets 📐ML Theory

TSN-Affinity: Similarity-Driven Parameter Reuse for Continual Offline Reinforcement Learning 🤖Machine Learning

NeuroPlastic: A Plasticity-Modulated Optimizer for Biologically Inspired Learning Dynamics 🧠Neural Networks

Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignment 📐ML Theory

Dynamical Priors as a Training Objective in Reinforcement Learning 📐ML Theory

Quantum Grover Adaptive Search for Discrete Simulation Optimization 📐ML Theory

How Fast Should a Model Commit to Supervision? Training Reasoning Models on the Tsallis Loss Continuum 📐ML Theory

Split over $n$ resource sharing problem: Are fewer capable agents better than many simpler ones? 🤖AI Agents

Safe-Support Q-Learning: Learning without Unsafe Exploration 🤖Machine Learning

SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning 🤖AI Agents

Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations 🤖AI Agents

Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty 🤖AI Agents

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