3,504 research outputs found
Lenia and Expanded Universe
We report experimental extensions of Lenia, a continuous cellular automata
family capable of producing lifelike self-organizing autonomous patterns. The
rule of Lenia was generalized into higher dimensions, multiple kernels, and
multiple channels. The final architecture approaches what can be seen as a
recurrent convolutional neural network. Using semi-automatic search e.g.
genetic algorithm, we discovered new phenomena like polyhedral symmetries,
individuality, self-replication, emission, growth by ingestion, and saw the
emergence of "virtual eukaryotes" that possess internal division of labor and
type differentiation. We discuss the results in the contexts of biology,
artificial life, and artificial intelligence.Comment: 8 pages, 5 figures, 1 table; submitted to ALIFE 2020 conferenc
A guided tour of asynchronous cellular automata
Research on asynchronous cellular automata has received a great amount of
attention these last years and has turned to a thriving field. We survey the
recent research that has been carried out on this topic and present a wide
state of the art where computing and modelling issues are both represented.Comment: To appear in the Journal of Cellular Automat
An evolutionary approach to the identification of Cellular Automata based on partial observations
In this paper we consider the identification problem of Cellular Automata
(CAs). The problem is defined and solved in the context of partial observations
with time gaps of unknown length, i.e. pre-recorded, partial configurations of
the system at certain, unknown time steps. A solution method based on a
modified variant of a Genetic Algorithm (GA) is proposed and illustrated with
brief experimental results.Comment: IEEE CEC 201
A framework for the local information dynamics of distributed computation in complex systems
The nature of distributed computation has often been described in terms of
the component operations of universal computation: information storage,
transfer and modification. We review the first complete framework that
quantifies each of these individual information dynamics on a local scale
within a system, and describes the manner in which they interact to create
non-trivial computation where "the whole is greater than the sum of the parts".
We describe the application of the framework to cellular automata, a simple yet
powerful model of distributed computation. This is an important application,
because the framework is the first to provide quantitative evidence for several
important conjectures about distributed computation in cellular automata: that
blinkers embody information storage, particles are information transfer agents,
and particle collisions are information modification events. The framework is
also shown to contrast the computations conducted by several well-known
cellular automata, highlighting the importance of information coherence in
complex computation. The results reviewed here provide important quantitative
insights into the fundamental nature of distributed computation and the
dynamics of complex systems, as well as impetus for the framework to be applied
to the analysis and design of other systems.Comment: 44 pages, 8 figure
Structural Design using Cellular Automata
Traditional parallel methods for structural design do not scale well. This paper discusses the application of massively scalable cellular automata (CA) techniques to structural design. There are two sets of CA rules, one used to propagate stresses and strains, and one to perform design analysis. These rules can be applied serially,periodically,or concurrently, and Jacobi or Gauss-
Seidel style updating can be done. These options are compared with respect to convergence,speed, and stability
Integrating a nanologic knowledge module Into an undergraduate logic design course
This work discusses a knowledge module in an undergraduate logic design course for electrical engineering (EE) and computer science (CS) students, that introduces them to nanocomputing concepts. This knowledge module has a twofold objective. First, the module interests students in the fundamental logical behavior and functionality of the nanodevices of the future, which will motivate them to enroll in other elective courses related to nanotechnology, offered in most EE and CS departments. Second, this module can be used to let students analyze, synthesize, and apply their existing knowledge of the Karnaugh-map-based Boolean logic reduction scheme into a revolutionary design context with majority logic. Where many efforts focus on developing new courses on nanofabrication and even nanocomputing, this work is designed to augment the existing standard EE and CS courses by inserting knowledge modules on nanologic structures so as to stimulate student interest without creating a significant diversion from the course framework
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