A hybrid scheme for action representation

Strong deficiencies are present in symbolic models for action representation and planning, regarding mainly the difficulty of coping with real, complex environments. These deficiencies can be attributed to several problems, such as the inadequacy in coping with incompletely structured situations, the difficulty of interacting with visual and motorial aspects, the difficulty in representing low‐level knowledge, the need to specify the problem at a high level of detail, and so on. Besides the purely symbolic approaches, several nonsymbolic models have been developed, such as the recent class of subsym‐bolic techniques. A promising paradigm for the modeling of reasoning, which combines features of both symbolic and analogical approaches, is based on the construction of analogical models of the reference for the internal representations, as introduced by Johnson‐Laird. In this work, we propose a similar approach to the problem of knowledge representation and reasoning about actions and plans. We propose a hybrid approach, symbolic and analogical, in which the inferences are partially devolved to measurements on analogical models generated starting from the symbolic representation. the interaction between the symbolic and the analogical level is due to the fact that procedures are connected to some symbols, allowing generating, updating, and verifying the mental model. the hybrid model utilizes, for the symbolic component, a representation system based on the distinction between terminological and assertional knowledge. the terminological component adopts a SI‐Net formalism, extended by temporal primitives. the assertional component is a subset of first‐order logics. the analogical representation is a set of concurrent procedures modeling parts of the world, action processes, simulations, and metaphors based on force fields concepts. A particular case study, regarding the problem of the assembly of a complex object from parts, is taken as an experimental paradigm. © 1993 John Wiley Sons, Inc.

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

[2]  Ronald J. Brachman,et al.  An overview of the KL-ONE Knowledge Representation System , 1985 .

[3]  Yoav Shoham,et al.  Temporal Logics in AI: Semantical and Ontological Considerations , 1987, Artif. Intell..

[4]  J. M. Larrazabal,et al.  Reasoning about change , 1991 .

[5]  Michael Brady,et al.  Artificial Intelligence and Robotics , 1985, Artif. Intell..

[6]  Ann Patricia Fothergill,et al.  An Interpreter for a Language for Describing Assemblies , 1980, Artif. Intell..

[7]  Yoav Shoham,et al.  Chronological Ignorance: Experiments in Nonmonotonic Temporal Reasoning , 1988, Artif. Intell..

[8]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[9]  D. McDermott A Temporal Logic for Reasoning About Processes and Plans , 1982, Cogn. Sci..

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

[11]  Bernard Meltzer,et al.  Analogical Representations of Naive Physics , 1989, Artif. Intell..

[12]  Ronald J. Brachman,et al.  What's in a Concept: Structural Foundations for Semantic Networks , 1977, Int. J. Man Mach. Stud..

[13]  Drew McDermott,et al.  Problems in Formal Temporal Reasoning , 1988, Artif. Intell..

[14]  Luc Steels Steps towards Common Sense , 1988, ECAI.

[15]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[16]  Richard W. Weyhrauch,et al.  Prolegomena to a Theory of Mechanized Formal Reasoning , 1980, Artif. Intell..

[17]  Ramanathan V. Guha,et al.  CYC: A Midterm Report , 1990, AI Mag..

[18]  John McCarthy,et al.  Circumscription - A Form of Non-Monotonic Reasoning , 1980, Artif. Intell..

[19]  Chris Tomlinson,et al.  Concurrent Object-Oriented Programming Languages , 1989, Object-Oriented Concepts, Databases, and Applications.

[20]  Hector J. Levesque,et al.  The Tractability of Subsumption in Frame-Based Description Languages , 1984, AAAI.

[21]  Giuseppe Marino,et al.  Motor Knowledge Representation , 1985, IJCAI.

[22]  James F. Allen Towards a General Theory of Action and Time , 1984, Artif. Intell..

[23]  Brian V. Funt,et al.  Problem-Solving with Diagrammatic Representations , 1980, Artif. Intell..

[24]  G. ADORNI,et al.  TOWARDS A DESCRIPTION OF ROBOT MOVEMENTS BY A QUASI-NATURAL LANGUAGE , 1984 .

[25]  Brian V. Funt,et al.  Analogical Modes of Reasoning and Process Modeling , 1983, Computer.

[26]  Bernhard Nebel,et al.  Computational Complexity of Terminological Reasoning in BACK , 1988, Artif. Intell..

[27]  Gianni Vercelli,et al.  Some Concepts on Analogic Planning in Assembly Tasks , 1990, ECAI.

[28]  Robert B. Tilove,et al.  Local obstacle avoidance for mobile robots based on the method of artificial potentials , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[29]  Gianni Vercelli,et al.  Analogic Models for Robot Programming , 1993 .

[30]  Drew McDermott,et al.  Non-Monotonic Logic I , 1987, Artif. Intell..