arXiv (All)
open access
World Action Planner: Generalizable Robot Decision-Making with Action-Conditioned World Models
Building generalizable robot agents for diverse applications remains a fundamental challenge. While imitation learning-based policies can perform well in familiar training environments, they often struggle to generalize to novel scenes, layouts, and task compositions. To this end, we present World A
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions#1249427
- World-Action Models for Robot Learning and Control: A Survey#1110464
- WorldScape Policy 2.0: Empowering Steerable World Action Modeling with Reasoning-Augmented Memory and In-Context Learning#1048747
- Forward Dynamics Models#1297469
- OGPO: Offline Goal-conditioned Policy Optimization for Recoverable Vision-Language-Action Models#1297266
Record · ID 1188290
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive