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Full-Text Articles in Physical Sciences and Mathematics
A Quantum Algorithm For Automata Encoding, Edison Tsai, Marek Perkowski
A Quantum Algorithm For Automata Encoding, Edison Tsai, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
Encoding of finite automata or state machines is critical to modern digital logic design methods for sequential circuits. Encoding is the process of assigning to every state, input value, and output value of a state machine a binary string, which is used to represent that state, input value, or output value in digital logic. Usually, one wishes to choose an encoding that, when the state machine is implemented as a digital logic circuit, will optimize some aspect of that circuit. For instance, one might wish to encode in such a way as to minimize power dissipation or silicon area. For …
On The Effect Of Criticality And Topology On Learning In Random Boolean Networks, Alireza Goudarzi
On The Effect Of Criticality And Topology On Learning In Random Boolean Networks, Alireza Goudarzi
Systems Science Friday Noon Seminar Series
Random Boolean networks (RBN) are discrete dynamical systems composed of N automata with a binary state, each of which interacts with other automata in the network. RBNs were originally introduced as simplified models of gene regulation. In this presentation, I will present recent work done conjointly with Natali Gulbahce (UCSF), Thimo Rohlf (MPI, CNRS), and Christof Teuscher (PSU). We extend the study of learning in feedforward Boolean networks to random Boolean networks (RBNs) and systematically explore the relationship between the learning capability, the network topology, the system size N, the training sample T, and the complexity of the computational task. …
Random Automata Networks: Why Playing Dice Is Not A Vice, Christof Teuscher
Random Automata Networks: Why Playing Dice Is Not A Vice, Christof Teuscher
Systems Science Friday Noon Seminar Series
Random automata networks consist of a set of simple compute nodes interacting with each other. In this generic model, one or multiple model parameters, such as the the node interactions and/or the compute functions, are chosen at random. Random Boolean Networks (RBNs) are a particular case of discrete dynamical automata networks where both time and states are discrete. While traditional RBNs are generally credited to Stuart Kauffman (1969), who introduced them as simplified models of gene regulation, Alan Turing proposed unorganized machines as early as 1948. In this talk I will start with Alan Turing's early work on unorganized machines, …
Life And Evolution In Computers, Melanie Mitchell
Life And Evolution In Computers, Melanie Mitchell
Computer Science Faculty Publications and Presentations
This paper argues for the possibility of 'artificial life' and computational evolution, first by discussing (via a highly simplified version) John von Neumann's self-reproducing automaton and then by presenting some recent work focusing on computational evolution, in which 'cellular automata', a form of parallel and decentralized computing system, are evolved via 'genetic algorithms'. It is argued that such in silico experiments can help to make sense of the question of whether we can eventually build computers that are intelligent and alive.
Revisiting The Edge Of Chaos: Evolving Cellular Automata To Perform Computations, Melanie Mitchell, Peter T. Hraber, James P. Crutchfield
Revisiting The Edge Of Chaos: Evolving Cellular Automata To Perform Computations, Melanie Mitchell, Peter T. Hraber, James P. Crutchfield
Computer Science Faculty Publications and Presentations
No abstract provided.