Artificial Life Models in Software

Transcription

1 Maciej Komosinski Andrew Adamatzky Editors Artificial Life Models in Software Second Edition ÖSpri inger

2 Contents Part I Virtual Environments 1 Avida: A Software Platform for Research in Computational Evolutionary Biology 3 Charles Ofria, David M. Bryson and Claus О. Wilke 1.1 Introduction to Avida History of Digital Life The Scientific Motivation for Avida The Avida Software Avida Organisms The Avida World Test Environments Performing Avida Experiments Analyze Mode A Summary of Avida Research The Evolution of Complex Features Survival of the Flattest Evolution of Digital Ecosystems Outlook 31 References 32 2 Foundations of and Recent Advances in Artificial Life Modeling with Repast 3 and Repast Simphony 37 Michael J. North and Charles M. Macal 2.1 Introduction Artificial Life Agent-Based Modeling for Artificial Life Chapter Organization REPAST Repast Repast Simphony 50 ix

3 x Contents Using Repast 3 and Repast Simphony Repast Artificial Life Models Conclusions 57 References 58 3 Sodarace: Continuing Adventures in Artificial Life 61 Peter W. McOwan and Edward J. Burton 3.1 The Sodarace Project Introduction Sodarace: The Story Begins Previous Work Sodarace, the Scientific Background Sodaconstructor: The Physics Engine of Sodarace Sodarace: The Racing Environmental Variables Taking Sodarace Out and About Software for Artificial Life in Sodarace Lessons Learned on Approaches for Artificial Life in Sodarace Easy-to-Use Point-and-Click Racing Amoebamatic: An Easy Start for the New Engineer AI and the Travelling Kiosk Software Interactions in Sodarace: The Evolution of the Forums Community Development of Peer-to-Peer Learning Web Sites The Pandora's Box: An Example of the Spontaneous Development of Scientific Method Interdisciplinary Interaction: Art and Music Meet Science and Engineering in Sodarace Sodarace in Schools Experiments with Sodarace Summary: The Future of Sodarace 76 References D Multi-Agent Simulations in the breve Simulation Environment 79 Jon Klein and Lee Spector 4.1 Overview Agent-Based Modeling Paradigms Comparison to Other Agent-Based Modeling Systems Motivations A Personal Motivation Design Principles and Goals Writing Simulations in breve Object Orientation and the Built-in breve Classes The Controller Object The breve Simulation Loop Defining Callbacks and Agent Behaviors 89

4 Contents xi The Steve Programming Language The Python Programming Language Breve Features and Technical Details D Spatial Simulation Physical Simulations Visualization The Push Programming Language Development History and Future Development Transition to Open Source Push Python Integration Future Development ALife/AI Research with breve Evolving Swarms Evolution of Cooperation Division Blocks Genetic Programming Research Educational Applications of breve Artificial Life and Braitenberg Vehicles Reactive Bouncy Balls for Kids Biology and SuperDuperWalker Artificial Intelligence in 3D Virtual Worlds Algorithmic Art Conclusion 104 References Pramsticks: Creating and Understanding Complexity of Life 107 Maciej Komosinski and Szymon Ulatowski 5.1 Available Software and Tools Simulation Ill Creature Model Ill The Three Modes of Body Simulation Ill Brain Receptors and Effectors Communication Environment Genetics and Evolution Scripting Creating Custom Script-Based Neurons Experiment Definitions Illustrative Example ("Standard Experiment" Definition) Popular Experiment Definitions Advanced Features for Research and Education 129

5 xii Contents Brain Analysis and Simplification Numerical Measure of Symmetry of Constructs Estimating Similarity of Creatures History of Evolution Vector Eye Fuzzy Control Research and Experiments Comparison of Genotype Encodings Automatic Optimization Versus Human Design Symmetry in Evolution and in Human Design Clustering with Similarity Measure Bio-Inspired Visual Coordination Understanding Evolved Behaviors Other Experiments Education with Entertainment Summary 146 References 147 Part II Lattice Worlds 6 StarLogo TNG: Making Agent-Based Modeling Accessible and Appealing to Novices 151 Eric Klopfer, Hal Scheintaub, Wendy Huang, and Daniel Wendel 6.1 Computational Modeling Simulations and Modeling in Schools Computer Programming Programming in Schools Original Design Criteria StarLogo StarLogo Limitations StarLogo: The Next Generation Spaceland StarLogoBlocks The StarLogo TNG Virtual Machine The Starting Point: StarLogo StarLogo TNG: The Next Step Forward An Addition in StarLogo TNG: Collisions StarLogo TNG Example Model Setup Seeding the Infection Motion Infection Recovery 172

6 6.6.6 Graphs Field Testing Learning Physics Through Programming From Models to Games Conclusion 180 References 181 From Artificial Life to In Silico Medicine: NetLogo as a Means of Translational Knowledge Representation in Biomedical Research 183 Gary An and Uri Wilensky 7.1 Introduction A Different Type of "Artificial Life" Modern Medicine and Limits of Reductionism: The Translational Challenge Agent-Based Dynamic Knowledge Representation and In Silico Laboratories Facilitating Dynamic Knowledge Representation: The NetLogo Toolkit Description and Origins of NetLogo Design Philosophy Behind NetLogo NetLogo Features NetLogo Models of Acute Inflammation NetLogo ABM of Intracellular Processes: The Response to Inflammatory Signals NetLogo ABM of In Vitro Gut Epithelial Barrier Experiments NetLogo ABM of Organ Function: Gut Ischemia and Inflammation NetLogo ABM of Multi-organ Interactions: The Gut-Pulmonary Axis of Inflammation Conclusion 208 References 209 Discrete Dynamics Lab: Tools for Investigating Cellular Automata and Discrete Dynamical Networks 215 Andrew Wuensche 8.1 Introduction What Is DDLab? A Brief History DDLab Updates Basins of Attraction Times for Attractor Basins Forward and Backward in Time DDLab's Interface and Initial Choices TFO, SEED, and FIELD Modes 228 xiii

7 xiv Contents 8.3 Network Parameters Value Range, v Network Size, n Neighborhood Size, к Dimensions Wiring or Connections Rule or Rule Mix Initial State, the Seed Network Architecture Wiring Graphic Wiring Matrix Network-Graph Running Space-Time Patterns and Attractor Basins Options for Space-Time Patterns Options for Attractor Basins Attractor Jump-Graph and Layout-Graph Mutation Learning and Forgetting Sequential Updating Vector PostScript of Graphic Output Filing Network Parameters, States, and Data Measures and Data Static Rule Measures Measures on Space-Time Patterns Measures on Attractor Basins Reverse Algorithms Chain-Rules and Dynamical Encryption DDLab Website, Manual, and Reviews 257 References EINSTein: A Multiagent-Based Model of Combat 259 Andrew Ilachinski 9.1 Background Land Combat as a Complex Adaptive System Agent-Based Modeling and Simulation EINSTein Features Source Code Design Philosophy Program Flow Combat Engine Agents Battlefield Agent Personalities Penalty Function 269

8 Contents xv Meta-rules Combat Run Modes Sample Patterns and Behavior Qualitative Classes of Behavior Lanchesterian Combat A Step Away from Lanchester Swarming Forces Nonmonotonicity Genetic Algorithm Breeding Search Space Mission Fitness EINSTein's GA Recipe Sample GA Breeding Experiment # Sample GA Breeding Experiment # Discussion Why Are Agent-Based Models of Combat Useful? Overview of Features in Newer Versions Agent Attributes Environment and Behavior Functions GUI and File I/O Python and wxwidgets Next Step 311 References 312 Part III Artificial Chemistries 10 From Artificial Chemistries to Systems Biology: Software for Chemical Organization Theory 319 Christoph Kaleta 10.1 Introduction Using Tools from Systems Biology: SBML and SBW Systems Biology Markup Language Systems Biology Workbench Chemical Organization Theory Background Algorithms for the Computation of Chemical Organizations Application of Chemical Organization Theory Software for the Computation of Chemical Organizations OrgAnalysis Other Applications for Organization Computation OrgView 337

9 xvi Contents Organization Computation on the Web Conclusion 340 References Spatially Resolved Artificial Chemistry 343 Harold Fellermann 11.1 Introduction Concepts Basic Principles of Coarse-Grained, Off-Lattice Simulation Techniques Interaction Potentials Thermostats Chemical Reactions Updating Schemes and Spatial Organization Applications Available Software and Tools ESPresSo Spartacus Smoldyn LAMMPS Conclusion 364 References 365 Part IV Artificial Life Arts 12 Simulated Breeding: A Framework of Breeding Artifacts on the Computer 371 Tatsuo Unemi 12.1 Introduction Basic Framework of IEC SBART and SBEAT SBART SBEAT Breeding in a Field Window Multifield User Interface Migration Among Fields Protection of Individual Effects of Multifiled Interface Partial Breeding Direct Genome Operation Production Samples Future Works Conclusion 391 References 391

10 Contents xvii 13 The Evolution of Sonic Ecosystems 393 Jon McCormack 13.1 Introduction Artificial Life Art Related Work Eden: An Artificial Life Artwork Agents and Environments The Eden World Agent Implementation Image Sound Interaction The Problem of Aesthetic Evolution Eden as a Reactive System Results Conclusion 412 References Enriching Aesthetics with Artificial Life 415 Alan Dorin 14.1 Introduction Wonder and the Sublime in Art and Nature Sublime Software The Betrayal of Points and Lines Moving Beyond Two Dimensions Spaces That Build Themselves An Ecosystemic Approach to Writing Artistic Software Conclusion 429 References 430 Appendix: Artificial Life Software 433 Index 439