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GenRL: Multimodal-foundation world models for generalization in embodied agents
Learning generalist embodied agents, able to solve multitudes of tasks in different domains is a long-standing problem.
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Learning Dynamic Attribute-factored World Models for Efficient Multi-object Reinforcement Learning
Often a task is a composition of previously learned tasks (e.g.
LearningGraphCellularAutomata
The transition rule is usually defined to update the state of each cell as a function of its current state and the state of its neighbours.
