On the power of synchronization
Journal of Information Processing and Cybernetics
Machine models and simulations
Handbook of theoretical computer science (vol. A)
Circuits of the mind
ACM SIGPLAN Notices
Why interaction is more powerful than algorithms
Communications of the ACM
Journal of the ACM (JACM)
Communications of the ACM
Proof, language, and interaction
Distributed Algorithms
Emergence of a Super-Turing Computational Potential in Artificial Living Systems
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
MFCS '00 Proceedings of the 25th International Symposium on Mathematical Foundations of Computer Science
The Computational Limits to the Cognitive Power of the Neuroidal Tabula Rasa
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
On the Power of Synchronization in Parallel Computations
MFCS '89 Proceedings on Mathematical Foundations of Computer Science 1989
Some connections between nonuniform and uniform complexity classes
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Relativistic Computers and Non-uniform Complexity Theory
UMC '02 Proceedings of the Third International Conference on Unconventional Models of Computation
Autopoietic automata: Complexity issues in offspring-producing evolving processes
Theoretical Computer Science
How We Think of Computing Today
CiE '08 Proceedings of the 4th conference on Computability in Europe: Logic and Theory of Algorithms
The Role of Agent Interaction in Models of Computing: Panelist Reviews
Electronic Notes in Theoretical Computer Science (ENTCS)
Computing by self-reproduction: autopoietic automata
UC'05 Proceedings of the 4th international conference on Unconventional Computation
On evolutionary lineages of membrane systems
WMC'05 Proceedings of the 6th international conference on Membrane Computing
The computational power of interactive recurrent neural networks
Neural Computation
The expressive power of analog recurrent neural networks on infinite input streams
Theoretical Computer Science
Information and Computation
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Modern networked computing systems follow scenarios that differ from those modeled by classical Turing machines. For example, their architecture and functionality may change over time as components enter or disappear. Also, as a rule their components interact with each other and with the environment at unpredictable times and in unpredictable manners, and they evolve in ways that are not pre-programmed. Finally, although the life span of the individual components may be finite, the life span of the systems as a whole is practically unlimited. The examples range from families of cognitive automata to (models of) the Internet and to communities of intelligent communicating agents.We present several models for describing the computational behaviour of evolving interactive systems, in order to characterize their computational power and efficiency. The analysis leads to new models of computation, including 'interactive' Turing machines (ITM's) with advice and new, natural characterizations of non-uniform complexity classes. We will argue that ITM's with advice can serve as an adequate reference model for capturing the essence of computations by evolving interactive systems, showing that 'in theory' the latter are provably more powerful than classical systems.