The Math Behind World Model Paradigms for Robot Learning
A mathematical analysis of IDM-style, Single-backbone-style, and MoT-style world-model paradigms in robot learning from the perspectives of probabilistic modeling, structured optimization, gradient conflict, and parameter coupling.