arXiv AI September 16, 2026 By Liang-Ching Tao, Pi-Chung Wang

Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging

The paper introduces LP‑BTS, a learning‑guided planning framework for mobile charging in large, dynamic action spaces. It uses a graph proposal policy to narrow candidate stops, a value critic to evaluate leaf nodes, and edge‑budgeted PUCT to compare short simulated futures before action selection. Experiments on a 30‑scenario battery‑life benchmark show LP‑BTS achieving the highest survival and alive‑AUC, outperforming domain‑engineered baselines and heuristic policies.

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arXiv AI

Sep 4

FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

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2d ago

LePlanner: An Iterative Amortized Controller For World Models

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By Saksham Bansal, Om Naphade, Chayan Aggarwal, Vrishin M

rag robotics multimodal

arXiv Machine Learning

Sep 1

Locally-Guided Actor-Critic: Training a Goal-conditioned Actor with a Subgoal-aware Critic

arXiv:2608.30406v1 Announce Type: new Abstract: Goal-conditioned reinforcement learning struggles with long horizons when rewards are sparse. While a planner can provide subgoals to guide a low-level...

By Olivier Serris, St\'ephane Doncieux, Olivier Sigaud

agents reinforcement-learning

arXiv AI

Aug 25

EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning

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By Can Xie, Yuyi Zhou, Wen Yang, Ziyi zhang, Siyao Song, Yingzhuo Deng, Shuo Ren, Jiajun Zhang

llms agents reinforcement-learning efficiency

arXiv Machine Learning

6d ago

T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks

The paper introduces T1, a 122‑billion‑parameter Mixture‑of‑Experts model trained with reinforcement learning to perform long‑horizon terminal tasks such as coding and scientific discovery. T1 operates a real shell in a cloud sandbox, making over 300 tool‑call turns per task and receiving rewards from task‑specific verifiers. The authors detail a training recipe that includes aggressive warm‑starting, TITO construction with drift repair, and rollout‑routing replay, achieving significant performance gains on Terminal‑Bench 2.1 and surpassing GPT‑5.4 and GLM‑5.1 on the Long‑Horizon Terminal Bench.

By Junyao Yang, Yucheng Shi, Zhongzhi Li, Ruhan Wang, Zongxia Li, Haitao Mi, Leowei Liang

llms agents reinforcement-learning benchmarks

arXiv Machine Learning

Jun 8

Latent Geometry Beyond Search: Amortizing Planning in World Models

arXiv:2605. 08732v2 Announce Type: replace-cross Abstract: Modern vision-based world models can represent observations as compact yet expressive latent manifolds, but fast goal-oriented planning in these spaces remains challenging.

By Hoang Nguyen, Xiaohao Xu, Xiaonan Huang

robotics benchmarks

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FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

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Locally-Guided Actor-Critic: Training a Goal-conditioned Actor with a Subgoal-aware Critic

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Latent Geometry Beyond Search: Amortizing Planning in World Models