Tagged articles

Long-Horizon Agents

5 articles · Page 1 of 1

Jul 27, 2026 · Artificial Intelligence

Dual‑Engine Evolution: A Systematic Survey of Long‑Horizon Agents

This 149‑page survey defines long‑horizon agents as a coupling of a base policy and a runtime harness (Agent = πθ ⊕ H), categorises task levels and capabilities, traces the field’s evolution from prompt to context to runtime engineering, and outlines a seven‑stage optimization pipeline, application forms, and frontier challenges, supported by empirical growth data and extensive references.

AI SurveyAgent OptimizationContext Engineering

0 likes · 12 min read

Dual‑Engine Evolution: A Systematic Survey of Long‑Horizon Agents

Machine Heart

Jul 25, 2026 · Artificial Intelligence

Towards Long-Horizon Agents: A 149‑Page Survey on Harness Engineering and Model Optimization

This survey analyzes over 900 works to define long‑horizon agents as a system‑level capability emerging from the co‑evolution of external harness engineering and internal model optimization, outlines key challenges, taxonomies, a three‑stage evolution, and future research directions.

AI SurveyAutonomous AgentsLong-Horizon Agents

0 likes · 20 min read

Towards Long-Horizon Agents: A 149‑Page Survey on Harness Engineering and Model Optimization

Machine Learning Algorithms & Natural Language Processing

Jul 16, 2026 · Artificial Intelligence

From Memory to Autonomous Research: Building Sustainable Long‑Horizon AI Agents

In this MLNLP academic talk, PhD student Hu Yuyang presents a comprehensive overview of long‑horizon agents, covering context management, memory systems, and autonomous research, and introduces his representative works SAM, AgentFugue, CompassMem, and Arbor that advance sustainable AI agents for real‑world tasks.

Autonomous ResearchContext ManagementLong-Horizon Agents

0 likes · 5 min read

From Memory to Autonomous Research: Building Sustainable Long‑Horizon AI Agents

PaperAgent

Jul 16, 2026 · Artificial Intelligence

Best Practices for Training Long‑Horizon Autonomous Agents

This article surveys recent Agentic RL research, extracts practical design principles, and details concrete implementations such as ToRL, AgentGym‑RL, Agent‑R1, StarPO, and AutoForge, highlighting reward design, environment interfaces, scaling strategies, and stability diagnostics for long‑horizon autonomous agents.

Agentic RLLong-Horizon AgentsReinforcement Learning

0 likes · 14 min read

Best Practices for Training Long‑Horizon Autonomous Agents

Data Party THU

Apr 20, 2026 · Artificial Intelligence

How MemPO Uses Reinforcement Learning to Turn Agent Memory into a Trainable Policy

MemPO introduces a self‑memory policy optimization framework that lets long‑horizon LLM agents autonomously manage and refine their memory via reinforcement learning, using global‑trajectory and informative‑memory advantage estimates, achieving up to 25.98% F1 gain and 73% token reduction on benchmark tasks.

LLMLong-Horizon AgentsMemPO

0 likes · 8 min read

How MemPO Uses Reinforcement Learning to Turn Agent Memory into a Trainable Policy