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adamatzky handbook unconventional computing theory implementations 2021

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Textbook in PDF format Did you know that computation can be implemented with cytoskeleton networks, chemical reactions, liquid marbles, plants, polymers and dozens of other living and inanimate substrates? Do you know what is reversible computing or a DNA microscopy? Are you aware that randomness aids computation? Would you like to make logical circuits from enzymatic reactions? Have you ever tried to implement digital logic with Minecraft? Do you know that eroding sandstones can compute too?This volume reviews most of the key attempts in coming up with an alternative way of computation. In doing so, the authors show that we do not need computers to compute and we do not need computation to infer. It invites readers to rethink the computer and computing, and appeals to computer scientists, mathematicians, physicists and philosophers. The topics are presented in a lively and easily accessible manner and make for ideal supplementary reading across a broad range of subjects. Theory Mapping the Territory of Computation Including Embodied Computation Unconventional Computation Implications Computation in General Topology of information representation Topology of information processing Programmability Universality Embodied Computation Definition Physics for computational purposes Transduction Analog computation Quantum computation Field computation Computation for physical purposes Programmable Matter Artificial Morphogenesis Conclusions Reversible Logic Element with Memory as an Alternative Logical Device Reversible Logic Element with Memory (RLEM) Definition of a reversible logic element with memory Rotary element (RE), a typical RLEM Constructing reversible machines by REs All Non-degenerate -State RLEMs Except Four are Universal Realizing RLEMs in Reversible Environments RLEMs in the billiard ball model RLEM in a simple reversible cellular automaton Concluding Remarks Space Bounded Scatter Machines First Concepts and Promised Results The Experiment, the Protocols and the Machine The Standard Scatter Machine Probabilistic trees Sparse oracles Coding and decoding the vertex position Lower bounds Upper bounds The Generalized Scatter Machine Lower bounds Upper bounds Exclusively Quantum: Computations Only Possible on a Quantum Computer Background: Parallelism and Quantum Theory On the importance of parallelism Quantum computation and quantum information The qubit Measurements Putting qubits together Entanglement Some History Quantum versus classical computation A review of previous results True randomness Entangled states Quantum speed-up Quantum simulations QTM versus DTM and PTM Quantum versus classical complexity Super-Turing computations Unconventional Computations and Non-universality Evolving Computations Evolving computational complexity Rank-varying computational complexity Time-varying computational complexity Evolving computational variables Time-varying variables Interacting variables Computations obeying a global constraint Quantum Fourier Transform Rank-varying complexity Semi-classical solution Parallel approach Quantum decoherence Time-varying variables Quantum Error-correction Quantum codes Time-varying complexity Error correction via symmetrization Entanglement Revisited Interacting variables Quantum distinguishability Generalization Another approach to distinguishability Some consequences Conveying quantum information through a classical channel Protecting quantum information from classical attacks Transformations obeying a global constraint Estimations of Integrated Information Based on Algorithmic Complexity and Dynamic Querying Basic Concepts of Integrated Information Theory Calculus of ϕ Methods Programmability test and meta-test Causal perturbation analysis Causal influence and sublog program-size divergence A simplicity versus complexity test Numerical Results Compression sensitivity as informative of integration Finding simple rules in complex behavior Simple rules and the black pattern of distribution of information Automatic meta-perturbation test Shrinking after dividing to rule Limitations Conclusions and Future Directions Appendix A A How a meta-perturbation test works Appendix B Robot Narratives Robots Explore an Alien Planet Prologue Greek Olympus, narrative robots Roman Olympus, declarative robots Epilogue Robot Imaginations Dennett’s Tower Robots in the tower An architecture for an ethical Popperian robot From Popperian to Gregorian robots Narrative logic Gregorian Chat The narrative hypothesis in more detail The Gregorian chat system Robot architecture Hybrid physical/virtual environment architecture Testing the narrative hypothesis in a robot ecology Extensions of the approach Discussion and Conclusions Communication and cognition Social robots Narrative logic and its interface with world modeling in artificial intelligence Beyond a “repository of actions”: The particular and the general in narrative Story generator and story parser Preparing for the future Evolving Boolean Regulatory Networks with Variable Gene Expression Times The RBNK Model The RBNK Model with Variable Gene Expression Times Gene expression Experimentation Asynchronous experimentation Variable Sized GRN with Variable Gene Expression Times Emergent complexity Experimentation Conclusions Membrane Computing Concepts, Theoretical Developments and Applications Types of P Systems Preliminaries Transition P systems P systems with active membranes Communication P systems Tissue-like P systems with symport/antiport rules Spiking neural P systems Enzymatic numerical P systems Computing Power and Computational Efficiency Computing power Rewriting membrane systems Computational efficiency Recognizer membrane systems Polynomial time complexity classes Limits on efficient computations Solving computationally hard problems Applications of Membrane Computing Modeling ecosystems with population dynamics P systems Path planning and control of mobile robots Fault diagnosis with spiking neural P systems Other applications Concluding remarks Implementation of P Systems Software implementations GPU-based hardware implementations GPU computing GPU simulators of P systems FPGA-based hardware implementations Discussion Concluding Remarks Computing with Modest Resources: How to Have Your Cake and Eat it Too Why Bigger is Not Necessarily Smarter Why Smaller Might be Smarter What is External Drive and How Does It Help A Thought Experiment: Maxwell’s Daemon Rebooted Example: Memristor Networks Memristor model Conclusions Physical Randomness Can Help in Computations Randomness is Important How Can We Describe Randomness in Precise Terms? Back to Physics How Does This Affect Computations Probabilistic Logic Gate in Asynchronous Game of Life with Critical Property Asynchronous Game of Life and its Logic Gates Phase transition and criticality Computation by asynchronous GL Logic gate in asynchronous GL Discussion Acknowledgements A Mystery of Human Biological Development — Can It Be Used to Speed up Computations? Formulation of the Problem Exponential Speedup Phenomenon: A Brief History and a Brief Description Symmetric Automata and Computations Structure of Abstract Automata and Instruction Machines Structure of Symmetric Automata and Machines Functional Characteristics of Operationally Symmetric Turing Machines Computation By Biological Means Computation Use of biology for computation What can biocomputers do? DNA Computing Origins of DNA computing Computing with DNA Adleman’s experiment Sticker systems Recent progress on computational power of DNA Limitations of DNA Computation with Slime Mould Introduction to slime moulds Slime moulds for computational tasks Amoeboid organisms as a computer Slime moulds as a form of computation Select applications of slime moulds Challenges of computing with slime moulds Computation with Motile Biological Agents Molecular motors Use of biological motion in confined structures Issues with mobile biologicals Computation with Synthetic Biology Chemotaxis Saccharum saccharomyces and genetic toggles Cellular computation Multicellular machines Differences in Biological Computing Paradigms Discussion Critical research gaps in biological computing The case for biosupremacy Swarm and Stochastic Computing for Global Optimization Optimization Stochastic Enhancements Evolutionary Computation Nature-Inspired Computing Non-SI-based approaches SI-based approaches Discussions Vector Computation Epistemology versus Ontology in the Quantum Computation Context Types of Quantum Oracles for Randomness: Pure States in a Superposition Versus Mixed States Questionable Parallelism by Views on a Vector Computation by Projective Measurements of Partitioned State Space Entanglement as Relational Parallelism Across Multi-Partite States On Partial Views of Vectors Unsupervised Learning Approach Using Reinforcement Techniques on Bio-inspired Topologies Molecular networks Cellular automata Conway’s Game-of-Life Neuromorphic computing systems Molecular-based Topology Artificial Neural Networks Neuron Model Simple Izhikevich model Excitation Reinforcement Majority-rule Game-of-Life rule Unsupervised Learning Majority-rule learning Game-of-Life learning Hebbian learning Training and Classification Results Discussion Acknowledgement Intelligent Gamesourcing — Artificial Intelligence in Problem Solution by Game Playing Gamesourcing History Motivation Leisure Game playing Paradigm Structure Fun Credibility of outputs Evaluation of success Current status Astro Drone EteRNA Foldit Play to cure: Genes in space Sea Hero Quest Application — People versus Differential Evolution in Search of the Shortest Path Volume : Implementations From Oscillatory Reactionsto Robotics: A Serendipitous Journey Through Chemistry, Physics and Computation Systems Dynamics as a Computational Platform Wet oscillating systems Electrochemical oscillators Computation and Control in Dynamic Systems Computation in memristive devices and systems Logic design with memristors/memristive devices Matrix vector multiplication Hardware artificial neural networks Principles of control in dynamic systems — PID case Reservoir computing Reservoir computing and control systems Controllers Beyond PID: Fuzzy and Neuromorphic Fuzzy logic Processing fuzzy logic by using molecules Implementation of fuzzy logic systems in solid-state devices Neuromorphic devices Alternative Computing in Autonomous Robotics Amoeba-based solution search system and electronic amoeba Amoeba-inspired autonomously walking robot Physicality for the identification of ground condition Integration of reinforcement learning for efficient walking Alternative Computing and Soft Robotics Concluding Remarks Computing by Chemistry: The Native Chemical Automata A Brief History How Native Chemical Automata are Built in Practice Selecting the language-automata pair, and the chemistry Initial conditions and alphabet symbol assignment Recipe quantification and selection of time interval Accept/reject criteria optimization Reconfiguration and Variants/Extension of Native Chemical Automata Inclusive hierarchy and automata reconfigurability Extension to continuous operation (CSTR reactor) Coupling of Belousov–Zhabotinsky to self-assembly Conclusions and Outlook Discovering Boolean Functions on Actin Networks The Actin Network Spike-based Gates Automaton model Interfacing with the network Maximizing a number of logical gates Actin droplet machine Voltage-based Gates The model Extension to bundle networks The network Preliminary results Results Ideal electrodes Boolean gates Realistic electrodes Finite state machine Using two values of k = and k = Discussion Implication and Not-Implication Boolean Logic Gates Mimicked with Enzyme Reactions — General Approach and Application to Signal-Triggered Biomolecule Release Processes Mimicking IMPLY Logic Gate Mimicking INHIB Logic Gate Using the IMPLY and INHIB Logic Gates for Stimulating Molecule Release Function Conclusions Appendix Molecular Computation via Polymerase Strand Displacement Reactions Logic circuits Chemical reaction networks organization Strand Displacement Using Strand Displacing Polymerase for Computation CRNs Using Strand Displacing Polymerase Methods and Protocol Oligonucleotide design, synthesis, and purification Fluorescence sample preparation and measurement Discussion and Outlook Optics-Free Imaging with DNA Microscopy: An Overview DNA Microscopy for Surface D Imaging DNA Microscopy for Volumetric D Imaging Conclusions and Outlook Fully Analog Memristive Circuits for Optimization Tasks: A Comparison Dynamical Equation for Memristor Circuits Single memristor and Lyapunov function Circuits Lyapunov function for memristor circuits Number of fixed points and stability Analysis and Comparisons The instances Minimization of the continuous Lyapunov function Conclusions Organic Memristive Devices for Bio-inspired Applications Organic Memristive Device Adaptive Circuits Relationship of Optical and Electrical Properties Neuromorphic Applications Frequency dependent plasticity Nervous system mimicking circuits Towards synapse prosthesis Stochastic self-organized computational systems Conclusions On Wave-Based Majority Gates with Cellular Automata Propagation Patterns in Life-like Rules MAJORITY Gates by Competing Patterns Final Notes Information Processing in Plants: Hormones as Integrators of External Cues into Plant Development Hormonal Encoding of Environmental Information Self-regulatory Hormonal Network Underlying Plasticity in Plant Development Information processing in the transition from dormancy to germination Concluding Remarks Hybrid Computer Approach to Train a Machine Learning System A brief introduction to artificial intelligence and machine learning Analog versus digital computing Balancing an inverse pendulum using reinforcement learning The Analog Simulation The Reinforcement Learning System Value function Q-learning algorithm Python implementation States Actions Modeling the action value function Q(s, a) Feature transformation to avoid underfitting Decaying α and ε to improve learning and to avoid overfitting Hybrid interface Results Acknowledgement On the Optimum Geometry and Training Strategy for Chemical Classifiers that Recognize the Shape of a Sphere The Evolutionary Optimization of Chemical Classifiers Results Conclusions Sensing and Computing with Liquid Marbles Collision-based Gate Belousov–Zhabotinsky Cargo Photosensor Thermal Sensor Robot Controller Neuromorphic Marbles Discussion Towards Colloidal Droplet Processors Background Data throughput Heat dissipation Energy consumption Liquid Droplet Computer Holonomic processors Colloidal Processors Phase change architectures Microfluidic circuits Layered shells Granular media, foams, and plasmas Biological Processors Conclusions Biomolecular Motor-based Computing Applications of Biomolecular Motors in Computing Parallel computing using biomolecular motors in nanofabricated networks Computing using swarm robots prepared from biomolecular motors Design and construction of molecular robots Swarming of molecular robots Controlling the shape morphology of swarms of molecular robots Remote control of the swarming of molecular robots Logical operation of molecular robots Orthogonal swarming of molecular robots Conclusions and Future Perspectives Computing with Square Electromagnetic Pulses Background Brief historical retrospective Basics of transmission line theory Method Main computing elements: Cross-points Four-point crossing: Catt’s junction Scattering matrix approach Multi-way junctions: Series and parallel Simulation results Scaling down geometries Pulse generation and control requirements Future Directions D-based structures Graph-based computing More complex signals and materials Acknowledgements Creative Quantum Computing: Inverse FFT Sound Synthesis, Adaptive Sequencing and Musical Composition Why Quantum Computer Music? Algorithmic Music qSyn: Inverse FFT Sound Synthesis qSeq: Adaptive Musical Sequencer The Composition Zeno Concluding Remarks Appendix Logical Gates in Natural Erosion of Sandstone Modeling of Natural Erosion Specific Parameters Gates AND gate XOR gate One-bit half-adder Discussion Supplementary Materials A Case of Toy Computing Implementing Digital Logics with “Minecraft” History and Theory of Toy Computing Digital Logics in “Minecraft” Signal generation and transportation NAND gates Digital Circuits in “Minecraft” and the Remains of Electronics The circuit The 4-bit full adder build with TTL-logic The 4-bit full adder build in “Minecraft” Project Discussion Building a BCD decoder in “Minecraft” The computational labyrinth Walking the way of the signal Evolving Conductive Polymer Neural Networks on Wetware Introduction of Polymer Neural Networks Electropolymerisation of Conducting Polymer Wire Polymer wire growth Wire diameter and growth rate Conductance increase of wires Directional growth of wire and D growth Machine Learning for Polymer Wire Growth Supervised learning: Simple perceptron for simple logic gates Unsupervised learning: Autoencoder for feature extraction Conclusions

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adamatzky handbook unconventional computing theory implementations 2021

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