AI RESEARCH
Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations
arXiv CS.LG
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ArXi:2605.14937v1 Announce Type: new Predictive world models enable agents to model scene dynamics and reason about the consequences of their actions. Inspired by human perception, object-centric world models capture scene dynamics using object-level representations, which can be used for downstream applications such as action planning. However, most object-centric world models and reinforcement learning (RL) approaches learn reactive policies that are fixed at inference time, limiting generalization to novel situations.