University of Southern Denmark Object-Action Complexes : Grounded Abstractions of Sensorimotor Processes

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.

[1]  Moshe Y. Vardi,et al.  Verification , 1917, Handbook of Automata Theory.

[2]  R. Hetherington The Perception of the Visual World , 1952 .

[3]  Arthur L. Samuel,et al.  Some Studies in Machine Learning Using the Game of Checkers , 1967, IBM J. Res. Dev..

[4]  C. Cordell Green,et al.  Application of Theorem Proving to Problem Solving , 1969, IJCAI.

[5]  H. C. LONGUET-HIGGINS,et al.  Non-Holographic Associative Memory , 1969, Nature.

[6]  W. E. Kock,et al.  Holography , 1971, Science.

[7]  Richard Fikes,et al.  STRIPS: A New Approach to the Application of Theorem Proving to Problem Solving , 1971, IJCAI.

[8]  Earl D. Sacerdoti,et al.  The Nonlinear Nature of Plans , 1975, IJCAI.

[9]  P. L. Adams THE ORIGINS OF INTELLIGENCE IN CHILDREN , 1976 .

[10]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[11]  V. Braitenberg Vehicles, Experiments in Synthetic Psychology , 1984 .

[12]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[13]  E. Reed The Ecological Approach to Visual Perception , 1989 .

[14]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[15]  Leslie Pack Kaelbling,et al.  Learning Functions in k-DNF from Reinforcement , 1990, ML.

[16]  Rodney A. Brooks,et al.  Elephants don't play chess , 1990, Robotics Auton. Syst..

[17]  Tony Plate,et al.  Holographic Reduced Representations: Convolution Algebra for Compositional Distributed Representations , 1991, IJCAI.

[18]  Michael I. Jordan,et al.  Task Decomposition Through Competition in a Modular Connectionist Architecture: The What and Where Vision Tasks , 1990, Cogn. Sci..

[19]  Rodney A. Brooks,et al.  Intelligence Without Reason , 1991, IJCAI.

[20]  David J. Spiegelhalter,et al.  Bayesian analysis in expert systems , 1993 .

[21]  R. Mishra,et al.  Self-Organization , 2021, Encyclopedic Dictionary of Archaeology.

[22]  Thomas A. Henzinger,et al.  The theory of hybrid automata , 1996, Proceedings 11th Annual IEEE Symposium on Logic in Computer Science.

[23]  Thomas G. Dietterich What is machine learning? , 2020, Archives of Disease in Childhood.

[24]  Günther Palm,et al.  Bidirectional Retrieval from Associative Memory , 1997, NIPS.

[25]  Kumpati S. Narendra,et al.  Adaptive control using multiple models , 1997, IEEE Trans. Autom. Control..

[26]  Michael A. Arbib,et al.  Schema-based learning: towards a theory of organization for biologically-inspired autonomous agents , 1997, AGENTS '97.

[27]  Leslie Pack Kaelbling,et al.  Planning and Acting in Partially Observable Stochastic Domains , 1998, Artif. Intell..

[28]  Yoav Freund,et al.  Large Margin Classification Using the Perceptron Algorithm , 1998, COLT.

[29]  Stevan Harnad The Symbol Grounding Problem , 1999, ArXiv.

[30]  A. Baddeley Essentials of Human Memory , 1999 .

[31]  R. Brooks,et al.  The cog project: building a humanoid robot , 1999 .

[32]  Roderic A. Grupen,et al.  A hybrid architecture for adaptive robot control , 2000 .

[33]  Mitsuo Kawato,et al.  MOSAIC Model for Sensorimotor Learning and Control , 2001, Neural Computation.

[34]  Fahiem Bacchus,et al.  A Knowledge-Based Approach to Planning with Incomplete Information and Sensing , 2002, AIPS.

[35]  C. Miall Modular motor learning , 2002, Trends in Cognitive Sciences.

[36]  Benjamin Kuipers,et al.  Bootstrap learning for object discovery , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[37]  Alexander Stoytchev,et al.  Behavior-Grounded Representation of Tool Affordances , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[38]  Pedro M. Domingos,et al.  Learning the structure of Markov logic networks , 2005, ICML.

[39]  Eyal Amir,et al.  Learning Partially Observable Deterministic Action Models , 2005, IJCAI.

[40]  Maya Cakmak,et al.  To Afford or Not to Afford: A New Formalization of Affordances Toward Affordance-Based Robot Control , 2007, Adapt. Behav..

[41]  Roni Khardon,et al.  Noise Tolerant Variants of the Perceptron Algorithm , 2007, J. Mach. Learn. Res..

[42]  Giulio Sandini,et al.  A Survey of Artificial Cognitive Systems: Implications for the Autonomous Development of Mental Capabilities in Computational Agents , 2007, IEEE Transactions on Evolutionary Computation.

[43]  L. P. Kaelbling,et al.  Learning Symbolic Models of Stochastic Domains , 2007, J. Artif. Intell. Res..

[44]  Mark Steedman,et al.  Using Kernel Perceptrons to Learn Action Effects for Planning , 2008 .

[45]  Christopher W. Geib,et al.  Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning , 2008 .

[46]  Ales Ude,et al.  Learning primitive actions through object exploration , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.

[47]  Danica Kragic,et al.  Birth of the Object: Detection of Objectness and Extraction of Object Shape through Object-Action complexes , 2008, Int. J. Humanoid Robotics.

[48]  Dirk Kraft,et al.  Learning to grasp unknown objects based on 3D edge information , 2009, 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA).

[49]  Alexander Stoytchev,et al.  Some Basic Principles of Developmental Robotics , 2009, IEEE Transactions on Autonomous Mental Development.

[50]  Justus H. Piater,et al.  A Probabilistic Framework for 3D Visual Object Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[51]  Florentin Wörgötter,et al.  Cognitive agents - a procedural perspective relying on the predictability of Object-Action-Complexes (OACs) , 2009, Robotics Auton. Syst..

[52]  Justus H. Piater,et al.  Refining grasp affordance models by experience , 2010, 2010 IEEE International Conference on Robotics and Automation.

[53]  Danica Kragic,et al.  A strategy for grasping unknown objects based on co-planarity and colour information , 2010, Robotics Auton. Syst..

[54]  Andrew G. Barto,et al.  Intrinsically Motivated Hierarchical Skill Learning in Structured Environments , 2010, IEEE Transactions on Autonomous Mental Development.