Computation at the edge of chaos: phase transitions and emergent computation
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Evolving cellular automata to perform computations: mechanisms and impediments
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
A new kind of science
Causal architecture, complexity and self-organization in time series and cellular automata
Causal architecture, complexity and self-organization in time series and cellular automata
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
All else being equal be empowered
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Evolving spatiotemporal coordination in a modular robotic system
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Information transfer by particles in cellular automata
ACAL'07 Proceedings of the 3rd Australian conference on Progress in artificial life
Spatiotemporal anomaly detection in gas monitoring sensor networks
EWSN'08 Proceedings of the 5th European conference on Wireless sensor networks
Improving recurrent neural network performance using transfer entropy
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Information dynamics in small-world boolean networks
Artificial Life
Local measures of information storage in complex distributed computation
Information Sciences: an International Journal
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We quantify the local information dynamics at each spatiotemporal point in a complex system in terms of each element of computation: information storage, transfer and modification. Our formulation demonstrates that information modification (or non-trivial information processing) events can be locally identified where "the whole is greater than the sum of the parts". We apply these measures to cellular automata, providing the first quantitative evidence that collisions between particles therein are the dominant information modification events.