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cs.AI2026
Baba in Wonderland: Online Self-Supervised Dynamics Discovery for Executable World Models
SeungWon Seo, DongHeun Han, SeongRae Noh +1
Executable world models can be read, edited, executed, and reused for planning, but only if the program captures the environment's transition law rather than semantic shortcuts in…
cs.AI2026
From Assumptions to Actions: Turning LLM Reasoning into Uncertainty-Aware Planning for Embodied Agents
SeungWon Seo, SooBin Lim, SeongRae Noh +2
Embodied agents operating in multi-agent, partially observable, and decentralized environments must plan and act despite pervasive uncertainty about hidden objects and collaborator…
cs.AI2024
REVECA: Adaptive Planning and Trajectory-based Validation in Cooperative Language Agents using Information Relevance and Relative Proximity
SeungWon Seo, SeongRae Noh, Junhyeok Lee +3
We address the challenge of multi-agent cooperation, where agents achieve a common goal by cooperating with decentralized agents under complex partial observations. Existing cooper…