Logical depth and physical complexity
A half-century survey on The Universal Turing Machine
Learning hierarchies of abstraction spaces
Proceedings of the sixth international workshop on Machine learning
Artificial Intelligence
Speeding up problem solving by abstraction: a graph oriented approach
Artificial Intelligence - Special volume on empirical methods
Self-dissimilarity: an empirically observable complexity measure
Proceedings from the international conference on complex systems on Unifying themes in complex systems
Dominant Color Region Based Indexing for CBIR
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
A semantic theory of abstractions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Domain abstraction and limited reasoning
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
The abstraction/implementation model of problem reformulation
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Preserving consistency across abstraction mappings
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
Towards a practical theory of reformulation for reasoning about physical systems
Artificial Intelligence - Special volume on reformulation
Verifying the incorrectness of programs and automata
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Hierarchical heuristic search revisited
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Perceptual learning and abstraction in machine learning: an application to autonomous robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Information Theory
Formalizing the abstraction process in model-based diagnosis
SARA'07 Proceedings of the 7th International conference on Abstraction, reformulation, and approximation
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Abstraction is fundamental for both human and artificial reasoning. The word denotes different activities and process, but all are intuitively related to the notion of complexity/simplicity, which is as elusive a notion as abstraction. From an analysis of the literature on abstraction and complexity it clearly appears that it is unrealistic to find definitions valid in all disciplines and for all tasks. Hence, we consider a particular model of abstraction, and try to investigate how complexity measures could be mapped to it. Preliminary results show that abstraction and complexity are not monotonically coupled notions, and that complexity may either increase or decrease with abstraction according to the definition of both and to the specificities of the considered domain.