Appendix for " Learning Dynamic Attribute-Factored World Models for Efficient Multi-object Reinforcement Learning "

In this section, we first provide a summary of the notation in Table A2. Then we show an example of the environment described in the main paper, and how the learned graphs are connected in a single ground graphical model, as described in Figure A1.