Physarum machines: computers from slime mould
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New Jersey
World Scientific
[2010]
|
| Schriftenreihe: | World Scientific series on nonlinear science
volume 74 |
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 UER01 Volltext |
| Beschreibung: | Includes bibliographical references (p. 249-259) and index 1. From reaction-diffusion to Physarum computing. 1.1. Reaction-diffusion computers. 1.2. Limitations of reaction-diffusion computers. 1.3. Physarum polycephalum. 1.4. Physarum as encapsulated reaction-diffusion computer. 1.5. Dawn of Physarum computing -- 2. Experimenting with Physarum. 2.1. Where to get plasmodium of P. polycephalum. 2.2. Physarum farms. 2.3. Dishes and scanners. 2.4. Data input with food. 2.5. Substrates. 2.6. Nutrient-rich vs. non-nutrient substrates. 2.7. Sensing. 2.8. Modeling plasmodium. 2.9. Summary -- 3. Physarum solves mazes. 3.1. Multiple-site start. 3.2. Single-site start. 3.3. Summary -- 4. Plane tessellation. 4.1. The ubiquitous diagram. 4.2. Physarum construction of Voronoi diagram. 4.3. Summary -- 5. Oregonator model of Physarum growing trees. 5.1. What a BZ medium could not do. 5.2. Physarum and Oregonator. 5.3. Building trees with Oregonator. 5.4. Validating simulation by experiments. 5.5. Summary -- - 6. Does the plasmodium follow Toussaint hierarchy? 6.1. Proximity graphs. 6.2. Plasmodium network and Toussaint hierarchy. 6.3. Preparing for graph growing. 6.4. Growing graph from a single point. 6.5. Growing from all points. 6.6. Physarum hierarchy. 6.7. Summary -- 7. Physarum gates. 7.1. XOR gate anyone? 7.2. Ballistics of Physarum localizations. 7.3. Physarum gates. 7.4. Simulation of Physarum gates. 7.5. Simulated one-bit half-adder. 7.6. Why do we use a non-nutrient substrate? 7.7. Summary -- 8. Kolmogorov-Uspensky machine in plasmodium. 8.1. Physarum machines. 8.2. Example of Physarum machine solving simple task. 8.3. On parallelism. 8.4. Summary -- 9. Reconfiguring Physarum machines with attractants. 9.1. Fusion and multiplication of active zones. 9.2. Translating active zone. 9.3. Reconfiguration of Physarum machine. 9.4. Summary -- - 10. Programming Physarum machines with light. 10.1. Physarum and light. 10.2. Designing control domains. 10.3. Trees and waves. 10.4. Diverting plasmodium. 10.5. Inertia. 10.6. Multiplying plasmodium waves. 10.7. Foraging around obstacles. 10.8. Routing signals in Physarum machine. 10.9. Disobedience. 10.10. Summary -- 11. Routing Physarum with repellents. 11.1. Avoiding repellents on nutrient-rich substrate. 11.2. Operating on non-nutrient substrate. 11.3. Operation DEFLECT. 11.4. Operation MULTIPLY. 11.5. Operation MERGE. 11.6. Summary -- 12. Physarum manipulators. 12.1. Plasmodium on water surface. 12.2. Manipulating floating objects. 12.3. Summary -- 13. Physarum boats. 13.1. Random wandering. 13.2. Sliding. 13.3. Pushing. 13.4. Anchoring. 13.5. Propelling. 13.6. Cellular automaton model. 13.7. Physarum tugboat. 13.8. On failures. 13.9. Summary -- - 14. Manipulating substances with Physarum machine. 14.1. Operations with colored substances. 14.2. Transfer of substances to specified location. 14.3. Mixing substances. 14.4. Superpositions of TRANSFER and MIX operations. 14.5. Summary -- 15. Road planning with slime mould. 15.1. United Kingdom in a gel. 15.2. Development of transport links. 15.3. Weighted Physarum graphs. 15.4. Physarum vs. Department for Transport. 15.5. Proximity graphs and motorways. 15.6. Imitating disasters. 15.7. Summary A Physarum machine is a programmable amorphous biological computer experimentally implemented in the vegetative state of true slime mould Physarum polycephalum. It comprises an amorphous yellowish mass with networks of protoplasmic veins, programmed by spatial configurations of attracting and repelling gradients. This book demonstrates how to create experimental Physarum machines for computational geometry and optimization, distributed manipulation and transportation, and general-purpose computation. Being very cheap to make and easy to maintain, the machine also functions on a wide range of substrates and in a broad scope of environmental conditions. As such a Physarum machine is a 'green' and environmentally friendly unconventional computer. The book is readily accessible to a nonprofessional reader, and is a priceless source of experimental tips and inventive theoretical ideas for anyone who is inspired by novel and emerging non-silicon computers and robots. An account on Physarum Machines can be viewed at http://www.youtube.com/user/PhysarumMachines |
| Beschreibung: | 1 Online-Ressource (xiv, 266 p.) |
| ISBN: | 9789814327596 9814327581 981432759X |
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| 490 | 0 | |a World Scientific series on nonlinear science |v volume 74 | |
| 500 | |a Includes bibliographical references (p. 249-259) and index | ||
| 500 | |a 1. From reaction-diffusion to Physarum computing. 1.1. Reaction-diffusion computers. 1.2. Limitations of reaction-diffusion computers. 1.3. Physarum polycephalum. 1.4. Physarum as encapsulated reaction-diffusion computer. 1.5. Dawn of Physarum computing -- 2. Experimenting with Physarum. 2.1. Where to get plasmodium of P. polycephalum. 2.2. Physarum farms. 2.3. Dishes and scanners. 2.4. Data input with food. 2.5. Substrates. 2.6. Nutrient-rich vs. non-nutrient substrates. 2.7. Sensing. 2.8. Modeling plasmodium. 2.9. Summary -- 3. Physarum solves mazes. 3.1. Multiple-site start. 3.2. Single-site start. 3.3. Summary -- 4. Plane tessellation. 4.1. The ubiquitous diagram. 4.2. Physarum construction of Voronoi diagram. 4.3. Summary -- 5. Oregonator model of Physarum growing trees. 5.1. What a BZ medium could not do. 5.2. Physarum and Oregonator. 5.3. Building trees with Oregonator. 5.4. Validating simulation by experiments. 5.5. Summary -- | ||
| 500 | |a - 6. Does the plasmodium follow Toussaint hierarchy? 6.1. Proximity graphs. 6.2. Plasmodium network and Toussaint hierarchy. 6.3. Preparing for graph growing. 6.4. Growing graph from a single point. 6.5. Growing from all points. 6.6. Physarum hierarchy. 6.7. Summary -- 7. Physarum gates. 7.1. XOR gate anyone? 7.2. Ballistics of Physarum localizations. 7.3. Physarum gates. 7.4. Simulation of Physarum gates. 7.5. Simulated one-bit half-adder. 7.6. Why do we use a non-nutrient substrate? 7.7. Summary -- 8. Kolmogorov-Uspensky machine in plasmodium. 8.1. Physarum machines. 8.2. Example of Physarum machine solving simple task. 8.3. On parallelism. 8.4. Summary -- 9. Reconfiguring Physarum machines with attractants. 9.1. Fusion and multiplication of active zones. 9.2. Translating active zone. 9.3. Reconfiguration of Physarum machine. 9.4. Summary -- | ||
| 500 | |a - 10. Programming Physarum machines with light. 10.1. Physarum and light. 10.2. Designing control domains. 10.3. Trees and waves. 10.4. Diverting plasmodium. 10.5. Inertia. 10.6. Multiplying plasmodium waves. 10.7. Foraging around obstacles. 10.8. Routing signals in Physarum machine. 10.9. Disobedience. 10.10. Summary -- 11. Routing Physarum with repellents. 11.1. Avoiding repellents on nutrient-rich substrate. 11.2. Operating on non-nutrient substrate. 11.3. Operation DEFLECT. 11.4. Operation MULTIPLY. 11.5. Operation MERGE. 11.6. Summary -- 12. Physarum manipulators. 12.1. Plasmodium on water surface. 12.2. Manipulating floating objects. 12.3. Summary -- 13. Physarum boats. 13.1. Random wandering. 13.2. Sliding. 13.3. Pushing. 13.4. Anchoring. 13.5. Propelling. 13.6. Cellular automaton model. 13.7. Physarum tugboat. 13.8. On failures. 13.9. Summary -- | ||
| 500 | |a - 14. Manipulating substances with Physarum machine. 14.1. Operations with colored substances. 14.2. Transfer of substances to specified location. 14.3. Mixing substances. 14.4. Superpositions of TRANSFER and MIX operations. 14.5. Summary -- 15. Road planning with slime mould. 15.1. United Kingdom in a gel. 15.2. Development of transport links. 15.3. Weighted Physarum graphs. 15.4. Physarum vs. Department for Transport. 15.5. Proximity graphs and motorways. 15.6. Imitating disasters. 15.7. Summary | ||
| 500 | |a A Physarum machine is a programmable amorphous biological computer experimentally implemented in the vegetative state of true slime mould Physarum polycephalum. It comprises an amorphous yellowish mass with networks of protoplasmic veins, programmed by spatial configurations of attracting and repelling gradients. This book demonstrates how to create experimental Physarum machines for computational geometry and optimization, distributed manipulation and transportation, and general-purpose computation. Being very cheap to make and easy to maintain, the machine also functions on a wide range of substrates and in a broad scope of environmental conditions. As such a Physarum machine is a 'green' and environmentally friendly unconventional computer. The book is readily accessible to a nonprofessional reader, and is a priceless source of experimental tips and inventive theoretical ideas for anyone who is inspired by novel and emerging non-silicon computers and robots. An account on Physarum Machines can be viewed at http://www.youtube.com/user/PhysarumMachines | ||
| 650 | 7 | |a SCIENCE / Life Sciences / Mycology |2 bisacsh | |
| 650 | 4 | |a Mathematisches Modell | |
| 650 | 4 | |a Biocomputers |x Mathematical models | |
| 650 | 4 | |a Physarum polycephalum |x Computer simulation | |
| 650 | 4 | |a Myxomycetes | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-981-4327-58-9 |
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Datensatz im Suchindex
| _version_ | 1804175591111393280 |
|---|---|
| any_adam_object | |
| author | Adamatzsky, Andrew |
| author_facet | Adamatzsky, Andrew |
| author_role | aut |
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| building | Verbundindex |
| bvnumber | BV043141528 |
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| dewey-full | 579.520113 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 579 - Microorganisms, fungi & algae |
| dewey-raw | 579.520113 |
| dewey-search | 579.520113 |
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| dewey-tens | 570 - Biology |
| discipline | Biologie |
| format | Electronic eBook |
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| id | DE-604.BV043141528 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:18:43Z |
| institution | BVB |
| isbn | 9789814327596 9814327581 981432759X |
| language | English |
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| record_format | marc |
| series2 | World Scientific series on nonlinear science |
| spelling | Adamatzsky, Andrew Verfasser aut Physarum machines computers from slime mould Andrew Adamatzky New Jersey World Scientific [2010] 1 Online-Ressource (xiv, 266 p.) txt rdacontent c rdamedia cr rdacarrier World Scientific series on nonlinear science volume 74 Includes bibliographical references (p. 249-259) and index 1. From reaction-diffusion to Physarum computing. 1.1. Reaction-diffusion computers. 1.2. Limitations of reaction-diffusion computers. 1.3. Physarum polycephalum. 1.4. Physarum as encapsulated reaction-diffusion computer. 1.5. Dawn of Physarum computing -- 2. Experimenting with Physarum. 2.1. Where to get plasmodium of P. polycephalum. 2.2. Physarum farms. 2.3. Dishes and scanners. 2.4. Data input with food. 2.5. Substrates. 2.6. Nutrient-rich vs. non-nutrient substrates. 2.7. Sensing. 2.8. Modeling plasmodium. 2.9. Summary -- 3. Physarum solves mazes. 3.1. Multiple-site start. 3.2. Single-site start. 3.3. Summary -- 4. Plane tessellation. 4.1. The ubiquitous diagram. 4.2. Physarum construction of Voronoi diagram. 4.3. Summary -- 5. Oregonator model of Physarum growing trees. 5.1. What a BZ medium could not do. 5.2. Physarum and Oregonator. 5.3. Building trees with Oregonator. 5.4. Validating simulation by experiments. 5.5. Summary -- - 6. Does the plasmodium follow Toussaint hierarchy? 6.1. Proximity graphs. 6.2. Plasmodium network and Toussaint hierarchy. 6.3. Preparing for graph growing. 6.4. Growing graph from a single point. 6.5. Growing from all points. 6.6. Physarum hierarchy. 6.7. Summary -- 7. Physarum gates. 7.1. XOR gate anyone? 7.2. Ballistics of Physarum localizations. 7.3. Physarum gates. 7.4. Simulation of Physarum gates. 7.5. Simulated one-bit half-adder. 7.6. Why do we use a non-nutrient substrate? 7.7. Summary -- 8. Kolmogorov-Uspensky machine in plasmodium. 8.1. Physarum machines. 8.2. Example of Physarum machine solving simple task. 8.3. On parallelism. 8.4. Summary -- 9. Reconfiguring Physarum machines with attractants. 9.1. Fusion and multiplication of active zones. 9.2. Translating active zone. 9.3. Reconfiguration of Physarum machine. 9.4. Summary -- - 10. Programming Physarum machines with light. 10.1. Physarum and light. 10.2. Designing control domains. 10.3. Trees and waves. 10.4. Diverting plasmodium. 10.5. Inertia. 10.6. Multiplying plasmodium waves. 10.7. Foraging around obstacles. 10.8. Routing signals in Physarum machine. 10.9. Disobedience. 10.10. Summary -- 11. Routing Physarum with repellents. 11.1. Avoiding repellents on nutrient-rich substrate. 11.2. Operating on non-nutrient substrate. 11.3. Operation DEFLECT. 11.4. Operation MULTIPLY. 11.5. Operation MERGE. 11.6. Summary -- 12. Physarum manipulators. 12.1. Plasmodium on water surface. 12.2. Manipulating floating objects. 12.3. Summary -- 13. Physarum boats. 13.1. Random wandering. 13.2. Sliding. 13.3. Pushing. 13.4. Anchoring. 13.5. Propelling. 13.6. Cellular automaton model. 13.7. Physarum tugboat. 13.8. On failures. 13.9. Summary -- - 14. Manipulating substances with Physarum machine. 14.1. Operations with colored substances. 14.2. Transfer of substances to specified location. 14.3. Mixing substances. 14.4. Superpositions of TRANSFER and MIX operations. 14.5. Summary -- 15. Road planning with slime mould. 15.1. United Kingdom in a gel. 15.2. Development of transport links. 15.3. Weighted Physarum graphs. 15.4. Physarum vs. Department for Transport. 15.5. Proximity graphs and motorways. 15.6. Imitating disasters. 15.7. Summary A Physarum machine is a programmable amorphous biological computer experimentally implemented in the vegetative state of true slime mould Physarum polycephalum. It comprises an amorphous yellowish mass with networks of protoplasmic veins, programmed by spatial configurations of attracting and repelling gradients. This book demonstrates how to create experimental Physarum machines for computational geometry and optimization, distributed manipulation and transportation, and general-purpose computation. Being very cheap to make and easy to maintain, the machine also functions on a wide range of substrates and in a broad scope of environmental conditions. As such a Physarum machine is a 'green' and environmentally friendly unconventional computer. The book is readily accessible to a nonprofessional reader, and is a priceless source of experimental tips and inventive theoretical ideas for anyone who is inspired by novel and emerging non-silicon computers and robots. An account on Physarum Machines can be viewed at http://www.youtube.com/user/PhysarumMachines SCIENCE / Life Sciences / Mycology bisacsh Mathematisches Modell Biocomputers Mathematical models Physarum polycephalum Computer simulation Myxomycetes Erscheint auch als Druck-Ausgabe 978-981-4327-58-9 http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=374800 Aggregator Volltext |
| spellingShingle | Adamatzsky, Andrew Physarum machines computers from slime mould SCIENCE / Life Sciences / Mycology bisacsh Mathematisches Modell Biocomputers Mathematical models Physarum polycephalum Computer simulation Myxomycetes |
| title | Physarum machines computers from slime mould |
| title_auth | Physarum machines computers from slime mould |
| title_exact_search | Physarum machines computers from slime mould |
| title_full | Physarum machines computers from slime mould Andrew Adamatzky |
| title_fullStr | Physarum machines computers from slime mould Andrew Adamatzky |
| title_full_unstemmed | Physarum machines computers from slime mould Andrew Adamatzky |
| title_short | Physarum machines |
| title_sort | physarum machines computers from slime mould |
| title_sub | computers from slime mould |
| topic | SCIENCE / Life Sciences / Mycology bisacsh Mathematisches Modell Biocomputers Mathematical models Physarum polycephalum Computer simulation Myxomycetes |
| topic_facet | SCIENCE / Life Sciences / Mycology Mathematisches Modell Biocomputers Mathematical models Physarum polycephalum Computer simulation Myxomycetes |
| url | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=374800 |
| work_keys_str_mv | AT adamatzskyandrew physarummachinescomputersfromslimemould |