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Recent research has established the effectiveness of machine learning for data-driven prediction of the future evolution of unknown dynamical systems, including chaotic systems. However, these approaches require large amounts of measured…

Machine Learning · Computer Science 2021-10-11 Daniel Canaday , Andrew Pomerance , Michelle Girvan

We present the first experimental realization of a ratchet cellular automaton (RCA) which has been recently suggested as an alternative approach for performing logical operations with interacting (quasi) particles. Our study was performed…

Soft Condensed Matter · Physics 2009-11-11 Dusan Babic , Clemens Bechinger

This paper reports on the application of sequence analysis algorithms for agents in robotic soccer and a suitable representation is proposed to achieve this mapping. The objective of this research is to generate novel better in-game…

Multiagent Systems · Computer Science 2014-01-13 P. Kiran Sree , G. V. S. Raju , S. Viswandha Raju , N. S. S. S. N Usha Devi

Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy --- even on parallel processors --- unlike the classical (deterministic) alternatives. We adapt one of…

Computation · Statistics 2011-12-23 Nathan Halko , Per-Gunnar Martinsson , Yoel Shkolnisky , Mark Tygert

Reservoir Computing (RC) models, a subclass of recurrent neural networks, are distinguished by their fixed, non-trainable input layer and dynamically coupled reservoir, with only the static readout layer being trained. This design…

Machine Learning · Computer Science 2024-08-16 Robert Simon Fong , Boyu Li , Peter Tiňo

This paper designs an efficient two-class pattern classifier utilizing asynchronous cellular automata (ACAs). The two-state three-neighborhood one-dimensional ACAs that converge to fixed points from arbitrary seeds are used here for pattern…

Cellular Automata and Lattice Gases · Physics 2016-02-01 Biswanath Sethi , Souvik Roy , Sukanta Das

Cellular automata (CA) are a class of computational models that exhibit rich dynamics emerging from the local interaction of cells arranged in a regular lattice. In this work we focus on a generalised version of typical CA, called graph…

Machine Learning · Computer Science 2021-10-28 Daniele Grattarola , Lorenzo Livi , Cesare Alippi

In this work, we propose a new approach towards the efficient optimization and implementation of reservoir computing hardware reducing the required domain expert knowledge and optimization effort. First, we adapt the reservoir input mask to…

Emerging Technologies · Computer Science 2018-10-31 Bogdan Penkovsky , Laurent Larger , Daniel Brunner

The Collatz, or 3x+1, Conjecture claims that for every positive integer n, there exists some k such that T^k(n)=1, where T is the Collatz map. We present three cellular automata (CA) that transform the global problem of mimicking the…

Number Theory · Mathematics 2013-01-15 Sitan Chen

After an apparent hiatus of roughly 30 years, we revisit a seemingly neglected subject in the theory of (one-dimensional) cellular automata: sublinear-time computation. The model considered is that of ACAs, which are language acceptors…

Computational Complexity · Computer Science 2020-06-11 Augusto Modanese

Reservoir computing is a recently introduced machine learning paradigm that has been shown to be well-suited for the processing of spatiotemporal data. Rather than training the network node connections and weights via backpropagation in…

Neural and Evolutionary Computing · Computer Science 2016-07-20 Ashley Prater

Cellular automata (CA) have been utilized for decades as discrete models of many physical, mathematical, chemical, biological, and computing systems. The most widely known form of CA, the elementary cellular automaton (ECA), has been…

Cellular Automata and Lattice Gases · Physics 2013-10-15 Lucas Kang

Quantum reservoir computing (QRC) exploits the information-processing capabilities of quantum systems to tackle time-series forecasting tasks, which is expected to be superior to their classical counterparts. By far, many QRC schemes have…

Quantum Physics · Physics 2025-02-25 Longhan Wang , Peijie Sun , Ling-Jun Kong , Yifan Sun , Xiangdong Zhang

Memristors are novel non volatile devices that manage to combine storing and processing capabilities in the same physical place.Their nanoscale dimensions and low power consumption enable the further design of various nanoelectronic…

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals. The performance of its analogue implementation are comparable to other state of the art algorithms for tasks such as speech recognition or…

Emerging Technologies · Computer Science 2018-02-09 Piotr Antonik , François Duport , Michiel Hermans , Anteo Smerieri , Marc Haelterman , Serge Massar

A Genetic Algorithm (GA) is proposed in which each member of the population can change schemata only with its neighbors according to a rule. The rule methodology and the neighborhood structure employ elements from the Cellular Automata (CA)…

Neural and Evolutionary Computing · Computer Science 2007-11-16 Vasileios Barmpoutis , Gary F. Dargush

Episodic memory is a psychology term which refers to the ability to recall specific events from the past. We suggest one advantage of this particular type of memory is the ability to easily assign credit to a specific state when remembered…

Machine Learning · Computer Science 2018-06-05 Kenny J. Young , Richard S. Sutton , Shuo Yang

In this paper we present a systematic view of Quantum Cellular Automata (QCA), a mathematical formalism of quantum computation. First we give a general mathematical framework with which to study QCA models. Then we present four different…

Quantum Physics · Physics 2007-05-23 Carlos A. Perez-Delgado , Donny Cheung

Robotic Process Automation (RPA) is a technology for automating repetitive routines consisting of sequences of user interactions with one or more applications. In order to fully exploit the opportunities opened by RPA, companies need to…

Artificial Intelligence · Computer Science 2020-01-07 Volodymyr Leno , Marlon Dumas , Marcello La Rosa , Fabrizio Maria Maggi , Artem Polyvyanyy

Approximate computing is an emerging computing paradigm that offers improved power consumption by relaxing the requirement for full accuracy. Since real-world applications may have different requirements for design accuracy, one trend of…

Hardware Architecture · Computer Science 2022-07-04 Jingxiao Ma , Sherief Reda