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This paper formalises Object-Action Complexes (OACs) as a basis for symbolic representations of sensorimotor experience and behaviours. OACs are designed to capture the interaction between objects and associated actions in artificial cognitive systems. This paper gives a formal definition of OACs, provides examples of their use for autonomous cognitive robots, and enumerates a number of critical learning problems in terms of OACs.

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In this paper, we analyze the different approaches taken to-date within the computer vision, the robotics and the artificial intelligence community for the representation, recognition, synthesis and understanding of action. We present a common framework for dealing with action at different levels of complexity and provide the reader with the necessary related literature references. We put the literature reference further into context and outline a unified interpretation of action by taking into account the different aspects from robotics, vision and AI.

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