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We address the problem of transferring grasp knowledge across objects and tasks. This means dealing with two important issues: 1) the induction of possible transfers, i.e., whether a given object affords a given task, and 2) the planning of a grasp that will allow the robot to fulfill the task. The induction of object affordances is approached by abstracting the sensory input of an object as a set of attributes that the agent can reason about through similarity and proximity. For graspdoi:10.1109/icra.2014.6907697 dblp:conf/icra/HjelmDEK14 fatcat:qn7aimvx25arfd5nshsg6o5emy