Object-Action Complexes (OACs) are proposed as a universal representation enabling effcient planning and execution of purposeful action at all levels of the cognitive architecture. OACs combine the representational and computational effciency for purposes of search (the frame problem) of STRIPS rules (Fikes 1971) and the object- and situation-oriented concept of affordance (Gibson 1950, Sahin et al. 2007) with the logical clarity of the event calculus (Kowalski et al. 1986, Steedman 2002). Aordance is the relation between a situation, usually including an object of a dened type, and the actions that it allows. While aordances have mostly been analyzed in their purely perceptual aspect, the OAC concept denes them more generally as state-transition functions suited to prediction. Such functions can be used for effcient forward-chaining planning, learning, and execution of actions represented simultaneously at multiple levels in an embodied agent architecture.
A first formal definition of an OAC in a multi-level hierarchy can be found in (Krueger et al, 2009) as well as a number of examples of OACs as well as examples how these OACs are embedded in more complex behaviors. The interplay between OACs across levels still remains to be defined properly on the basis of the examples being realized in PACO-PLUS. This final formalization will be done in the last year of the project.
Krüger, N., Piater, J., Wörgötter,F., Geib, Ch., Petrick, R., Steedman, M.; Ude, A., Asfour, T., Kraft, D., Omrcen, D., Hommel, B., Agostino, A., Kragic, D., Eklundh, J., Kruger, V., Torras, C. and Dillmann, R.(2009). A Formal Definition of Object Action Complexes and Examples at different Levels of the Process Hierarchy.
Wörgötter, F., Agostini, A., Krüger, N., Shylo, N. and Porr, B. Cognitive agents - a procedural perspective relying on the predictability of Object-Action-Complexes (OACs). Robotics and Autonomous Systems, 2008.
Geib, Ch., Mourao, K., Petrick, R., Pugeault, N., Steedman, M., Krüger, N. and Wörgötter, F. Object Action Complexes as an Interface for Planning and Robot Control. IEEE-RAS International Conference on Humanoid Robots (Humanoids 2006).
Justus Piater, Mark Steedman, Florentin Wörgötter. Learning in PACO-PLUS.