Learning Visual Predictive Models of Physics for Playing Billiards

international conference on learning representations, Volume abs/1511.07404, 2016.

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We have presented an object-centric prediction approach that exploits translation invariance in dynamics of physical systems to learn a dynamical model of the world directly from visual inputs

Abstract:

The ability to plan and execute goal specific actions in varied, unexpected settings is a central requirement of intelligent agents. In this paper, we explore how an agent can be equipped with an internal model of the dynamics of the external world, and how it can use this model to plan novel actions by running multiple internal simulat...More

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