Manual Intelligence as a Rosetta Stone for Robot Cognition

Ritter, Helge; Haschke, Robert; Röthling, Frank; Steil, Jochen J.

doi:10.1007/978-3-642-14743-2_12

Cited by 2 publications

(1 citation statement)

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“…Having studied aspects of this challenge using advanced robot platforms in the context of grasping and manipulation [2], we here wish to introduce a complementary approach whose aim is to provide a maximally parsimonious, yet very rich framework to study mechanisms of physics-based categorization. To this end we introduce a novel class of problems inspired by and extending earlier work on pattern categorization [3].…”

Section: Introductionmentioning

confidence: 99%

Physical Bongard Problems

Weitnauer

Ritter

2012

IFIP Advances in Information and Communication Technology

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In this paper, we introduce Physical Bongard Problems (PBPs) as a novel and potentially rich approach to study the impact the constraints of a physical world have on mechanisms of concept learning and scene categorization. Each PBP consists of a set of 2D physical scenes which are positive or negative examples of a concept that must be identified. We discuss the properties that make PBPs challenging, analyze computational and representational requirements for a computational solver, and describe a first implementation of such a system. It can solve a subset of non-trivial PBPs using a version space approach for achieving its scene categorizations. The key element is a physics engine that is used both for the construction of information-rich physical features and for the prediction of how a given situation might evolve.

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Section: Introductionmentioning

confidence: 99%