We had quite an extensive discussion about this paper after the author response. The reviewers appreciated the clarifications and especially the additional experiment. What makes the paper stand out is proposing two generic conditions that enforce the emergence of spatial structures and experimentally validating them. The discussion circled around Equation (1), how well that would hold for realistic (noisy) sensing and what the implication on the emergence of the spatial structures would be. To our understanding the later parts of the paper don't rely on this equation but only on the intuition. Nevertheless, it would be nice to include a discussion on the impact of realistic sensing. A few related papers that were mentioned by R1: [0] D. Pierce and B. Kuipers, "Map learning with uninterpreted sensors and effectors.," Artificial Intelligence , vol. 92, pp. 169–229, 1997. [1] J. Modayil, "Bootstrap Learning a Perceptually Grounded Object Ontology." 2004. [2] J. M. Benjamin Kuipers Patrick Beeson, "Bootstrap learning of foundational representations.," Connection Science , vol. 18, no. 2, pp. 145–158, Jun. 2006. [3] J. Modayil and B. Kuipers, "Autonomous Development of a Grounded Object Ontology by a Learning Robot.," in Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI-07) , 2007. [4] J. Modayil, "Discovering sensor space: Constructing spatial embeddings that explain sensor correlations," in Development and Learning (ICDL), 2010 IEEE 9th International Conference on , 2010, pp. 120–125. [5] A. M. Dearden and Y. Demiris, "Learning Forward Models for Robots.," in IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30-August 5, 2005 , 2005, pp. 1440–1445. [6] Y. Demiris and A. Dearden, "From motor babbling to hierarchical learning by imitation: a robot developmental pathway," in Proceedings Fifth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems , 2005, pp. 31–37. [7] D. Ognibene, F. Mannella, G. Pezzulo, G. Baldassarre. "Integrating Reinforcement-Learning, Accumulator Models, and Motor-Primitives to Study Action Selection and Reaching in Monkeys," Proceedings of the 7th International Conference on Cognitive Modelling, 2006 [8] D. Ognibene, A. Rega, G. Baldassarre, "A model of reaching that integrates reinforcement learning and population encoding of postures," From Animals to Animats 9: Proceedings of the Ninth International Conference, 2006