Special issue on artificial intelligence and symbolic computation
نویسندگان
چکیده
ing symbolic matrices Special issue on artificial intelligence and symbolic computation Randa Almomen · Alan P. Sexton · Volker Sorge © Springer Science+Business Media B.V. 2012 Abstract We present a procedure that allows the abstraction of elements in concrete symbolic matrices to obtain a more compact representation employing ellipses in order to expose homogeneous regions present in a matrix. We furthermore extend that procedure to allow for generalisations of concrete matrices to an abstract form that enables us to determine the generic type of a given matrix. The presented algorithms employ artificial intelligence techniques such as pattern recognition and constraint solving.We present a procedure that allows the abstraction of elements in concrete symbolic matrices to obtain a more compact representation employing ellipses in order to expose homogeneous regions present in a matrix. We furthermore extend that procedure to allow for generalisations of concrete matrices to an abstract form that enables us to determine the generic type of a given matrix. The presented algorithms employ artificial intelligence techniques such as pattern recognition and constraint solving.
منابع مشابه
The Grand Challenges and Myths of Neural-Symbolic Computation
The construction of computational cognitive models integrating the connectionist and symbolic paradigms of artificial intelligence is a standing research issue in the field. The combination of logic-based inference and connectionist learning systems may lead to the construction of semantically sound computational cognitive models in artificial intelligence, computer and cognitive sciences. Over...
متن کاملCompletion and Invariant Theory in Symbolic Computation and Artificial Intelligence
An outline for the study of invariant theoretic (as structural) and completion (as syntactical) concepts in symbolic computation and artiicial intelligence is presented on a level of abstraction which permits a unifying viewpoint on problems in symbolic computation and artiicial intelligence. We refer to applications in computational polynomial ideal theory and in general problem-solving in the...
متن کاملNeural-Symbolic Cognitive Reasoning - ReadingSample
The construction of robust computational models integrating reasoning and learning is a key research challenge for artificial intelligence. Recently, this challenge was also put forward as a fundamental problem in computer science [255]. Such a challenge intersects with another long-standing entry in the research agenda of artificial intelligence: the integration of its symbolic and connectioni...
متن کاملThe Expressive Power of Abstract-State Machines
Conventional computation models assume symbolic representations of states and actions. Gurevich’s “Abstract-State Machine” model takes a more liberal position: Any mathematical structure may serve as a state. This results in “a computational model that is more powerful and more universal than standard computation models” [5]. We characterize the Abstract-State Machine model as a special class o...
متن کاملComputational intelligence and soft computing: some thoughts on already explored and not yet explored paths
We comment upon the very essence, roots, potentials, and applicability of computational intelligence and soft computing. We followed a different path than those traditionally employed, and which are so well and in a deep and comprehensive way documented in other papers in this special issue. First, we consider relations between computational intelligence and artificial intelligence, starting fr...
متن کامل