Complex behavior in evolutionary robotics / / Lukas König

• Record Nr.: UNINA9910817699203321
• Autore: König Lukas
• Pubbl/distr/stampa: Boston : , : De Gruyter, , [2015]; ©2015
• ISBN: 1-5231-0453-8; 3-11-040855-4; 3-11-040918-6
• Descrizione fisica: 1 online resource (262 p.)
• Disciplina: 629.8/92
• Soggetti: Evolutionary robotics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Front matter -- Acknowledgements -- Contents -- List of Figures -- List of Tables -- List of Notations -- 1. Introduction -- 2. Robotics, Evolution and Simulation -- 3. The Easy Agent Simulation -- 4. Evolution Using Finite State Machines -- 5. Evolution and the Genotype-Phenotype Mapping -- 6. Data Driven Success Prediction of Evolution in Complex Environments -- 7. Conclusion -- References -- Index
• Sommario/riassunto: Es werden vier neue Lösungsansätze für Probleme aus dem Bereich Evolutionäre Robotik bzw. Agenten-Simulation wissenschaftlich untersucht. Von besonderem Interesse ist eine neuartige Methode zur Imitierung der natürlichen Evolution in ihrer Fähigkeit, die eigenen Mutations- und Rekombinationsoperationen während der Evolution von Robotern anzupassen.; Today, autonomous robots are used in a rather limited range of applications such as exploration of inaccessible locations, cleaning floors, mowing lawns etc. However, ongoing hardware improvements (and human fantasy) steadily reveal new robotic applications of significantly higher sophistication. For such applications, the crucial bottleneck in the engineering process tends to shift from physical boundaries to controller generation. As an attempt to automatize this process, Evolutionary Robotics has successfully been used to generate ; robotic controllers of various types. However, a major challenge of the field remains the evolution of truly complex behavior. Furthermore, automatically created controllers often lack analyzability which makes them useless for safety-critical applications. In this book, a simple controller model based on Finite State Machines is proposed which allows a straightforward analysis of evolved behaviors. To increase the model's evolvability, a procedure is introduced which, by adapting the genotype-phenotype mapping at runtime, efficiently traverses both the behavioral search space as well as (recursively) the search space of genotype-phenotype mappings. Furthermore, a data-driven mathematical framework is proposed which can be used to calculate the expected success of evolution in complex environments.

Computational Methods in Systems Biology : 13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings / / edited by Olivier Roux, Jérémie Bourdon

• Record Nr.: UNINA9910484714203321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
• ISBN: 3-319-23401-3
• Edizione: [1st ed. 2015.]
• Descrizione fisica: 1 online resource (XIX, 288 p. 81 illus.)
• Collana: Lecture Notes in Bioinformatics, , 2366-6331 ; ; 9308
• Disciplina: 570.285
• Soggetti: Bioinformatics; Computer science; Computer simulation; Software engineering; Computer science - Mathematics; Computational and Systems Biology; Theory of Computation; Computer Modelling; Software Engineering; Symbolic and Algebraic Manipulation
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Organization -- Invited Talks -- Estimation and Verification of Hybrid Heart Models for Personalised Medical and Wearable Devices -- More Thoughts on the Whole Organism Challenge -- A Genetically Modified Hoare Logic that Identifies the Parameters of a Gene Network -- Perspectives on Genome Scale Modelling of Metabolism -- Contents -- Invited Talks -- Estimation and Verification of Hybrid Heart Models for Personalised Medical and Wearable Devices -- 1 Heart Model and Personalisation -- 2 Applications and Discussion -- References -- A Genetically Modified Hoare Logic that Identifies the Parameters of a Gene Network -- 1 Thomas' Gene Regulatory Networks with Multiplexes -- 2 Hoare Triples for Gene Networks -- 3 A Hoare Logic for Gene Networks -- 4 Example -- References -- Regular Papers -- SReach: A Probabilistic Bounded Delta-Reachability Analyzer for Stochastic Hybrid Systems -- 1 Introduction -- 2 Stochastic Hybrid Models -- 3 SReach Algorithm -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Experimental Design for Inference over the A. thaliana Circadian Clock Network -- 1 Introduction -- 2 Methods -- 2.1 Bayesian Experimental Design -- 2.2 Frequency-Domain Model of Gene Expression Levels -- 2.3 Experimental Design for Estimating Parameters of a DSS Model -- 2.4 A. thaliana Circadian Clock Model -- 3 Results -- 4 Conclusions -- References -- Efficient Stochastic Simulation of Systems with Multiple Time Scales via Statistical Abstraction -- 1 Introduction -- 2 Background and Related Work -- 3 Quasi-Equilibrium Reduction -- 4 Approximation of Rate Expectations -- 4.1 Continuity of Rates of the Slow System -- 4.2 Exploring Rate Expectation via Pre-simulation Runs -- 4.3 Stochastic Simulation via Statistical Abstraction -- 5 Experimental Evaluation -- 5.1 Stiff Enzyme-Substrate Reaction.; 5.2 Viral Infection Model -- 6 Conclusions -- References -- Approximate Bayesian Computation for Stochastic Single-Cell Time-Lapse Data Using Multivariate Test Statistics -- 1 Introduction -- 2 Introduction to Approximate Bayesian Computation -- 3 ABC with Multivariate Test Statistics -- 3.1 Multivariate Test Statistics -- 3.2 Comparison of Test Statistics in ABC SMC for Samples of a Bivariate Normal Random Variable -- 4 Simulation Example: Gene Expression -- 4.1 Equilibrium and Non-Equilibrium Time-Series -- 4.2 Parameter Variability -- 4.3 Tree Structure -- 5 Discussion and Outlook -- References -- Stochastic Analysis of Chemical Reaction Networks Using Linear Noise Approximation -- 1 Introduction -- 2 Chemical Reaction Networks -- 3 Linear Noise Approximation -- 3.1 Probabilistic Analysis of CRNs -- 4 Stochastic Evolution Logic (SEL) -- 4.1 LNA-based Approximate Model Checking for CRNs -- 5 Experimental Results -- 6 Concluding Remarks -- References -- Adaptive Moment Closure for Parameter Inference of Biochemical Reaction Networks -- 1 Introduction -- 2 Stochastic Modeling of Biochemical Reaction Networks -- 3 Moment-Based Parameter Inference -- 4 Adaptive Approach for Parameter Inference -- 5 Case Studies -- 6 Discussion -- References -- Inferring Executable Models from Formalized Experimental Evidence -- 1 Introduction -- 2 About Pathway Logic and Datums -- 2.1 Pathway Logic -- 2.2 Datums: Formal Representation of Experimental Results -- 3 Inferring Rules from Datums: An Example -- 4 A Logical Specification for Datums -- 4.1 Assertions and Inference Rules for Datums -- 4.2 Mapping Datums to Assertions -- 5 Signaling Model of Hras Activation by Egf -- 6 Related Work and Conclusion -- References -- Symbolic Dynamics of Biochemical Pathways as Finite ; States Machines -- 1 Introduction -- 2 Monomolecular Networks with Totally Separated Constants.; 3 Tropical Equilibrations of Nonlinear Networks with Polynomial Rate Functions -- 4 Learning a Finite State Machine from a Nonlinear Biochemical Network -- 5 Conclusion -- References -- Feature Learning Using Stacked Autoencoders to Predict the Activity of Antimicrobial Peptides -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset and Descriptors -- 2.2 Autoencoders (AEs) -- 2.3 Stacked Autoencoder (SAE) -- 2.4 Processing Workflow -- 3 Experimental Setup -- 3.1 Experimental Configurations -- 3.2 Validation and Supervised Training -- 4 Results and Discussion -- 5 Conclusions -- References -- Structural Simplification of Chemical Reaction Networks Preserving Deterministic Semantics -- 1 Introduction -- 2 Preliminary Example -- 3 Reaction Networks -- 4 Contextual Equilibrium-Equivalence -- 5 Simplification Axioms -- 6 Simplification of the Tet-On Reaction Network -- 7 Conclusion -- References -- Automating the Development of Metabolic Network Models -- 1 Introduction -- 1.1 Adam, a Robot Scientist -- 1.2 Huginn -- 1.3 Metabolic Networks as Biological Mechanisms -- 2 Methods -- 2.1 Discovery of Mechanisms -- 2.2 Abductive Logic Programming -- 2.3 Representing Models Using Logic -- 2.4 Experiment Types and Predictions -- 2.5 Automating Crucial Tasks -- 3 Results and Conclusions -- 4 Related Work -- References -- Qualitative Reasoning for Reaction Networks with Partial Kinetic Information -- 1 Introduction -- 2 Reaction Networks -- 3 Modeling Language -- 4 Example: Regulation of Metabolism of B. subtilis -- 5 Similarity by Difference Abstraction -- 6 Abstract Interpretation to Difference Constraints -- 7 Qualitative Reasoning with Difference Constraints -- 8 Conclusion -- References -- Boolean Network Identification from Multiplex Time Series Data -- 1 Introduction -- 2 Boolean Network Identification.; 2.1 Admissible Boolean Networks and Multiplex Time Series Data -- 2.2 Over-Approximation of Boolean Network Verification -- 2.3 Optimization with Respect to Time Series Data -- 2.4 Implementation -- 3 Evaluation -- 3.1 Case Study -- 3.2 Benchmarks -- 3.3 Comparison with Inferences Using Pseudo Steady-States -- 4 Conclusion -- References -- BioPSy: An SMT-based Tool for Guaranteed Parameter Set Synthesis of Biological Models -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Personalized Prostate Cancer Treatment -- 3.2 Human Starvation -- 3.3 Cell Cycle -- 4 Conclusions and Future Work -- References -- Derivation of Qualitative Dynamical Models from Biochemical Networks -- 1 Introduction -- 2 Case Study -- 3 Trace Semantics -- 4 Derivation of a Coarse-Grained Qualitative Semantics -- 5 Refinements -- 5.1 Mass Invariants -- 5.2 Watching Interval Boundaries -- 5.3 Scales Separation -- 6 Conclusion -- References -- Model-Based Investigation of the Effect of the Cell Cycle on the Circadian Clock Through Transcription Inhibition During Mitosis -- 1 Introduction -- 2 Experimental Observations and Their Specification in Temporal Logic -- 2.1 Experimental Data -- 2.2 Temporal Logic Specification -- 3 Mathematical Models and Their Coupling -- 3.1 Model of the Cell Cycle -- 3.2 Models of the Circadian Clock -- 3.3 Coupling from the Cell Cycle to the Circadian Clock by the Inhibition of Transcription During Mitosis -- 4 Computational Results -- 4.1 Comparison to Experimental Data Without Dexamethasone -- 4.2 Comparison to Data with Dexamethasone -- 4.3 Remaining Paradox on Phase Data -- 5 Conclusion -- References -- Analysis of a Post-translational Oscillator Using Process Algebra and Spatio-Temporal Logic -- 1 Introduction -- 2 The Jolley PTO Model -- 3 Process Algebra Model Construction -- 3.1 Species -- 3.2 Interactions ; -- 3.3 Mixture -- 3.4 Validation.; 4 Basic Time Series Analysis -- 4.1 Coupled jPTOs -- 4.2 Weaker Coupling -- 4.3 Coupling Out of Phase -- 4.4 Perturbation -- 5 Model-Checking Experiments -- 5.1 Behaviour Under Composition -- 5.2 Complex Dynamics -- 5.3 Perturbation Response -- 5.4 Results -- 6 Conclusions -- A Basic Jolley Model -- B Coupled jPTOs Model -- C Weaker Coupled jPTOs -- D Driving Other Reactions -- E Perturbation -- References -- Modeling of Resilience Properties in Oscillatory Biological Systems Using Parametric Time Petri Nets -- 1 Introduction -- 1.1 Petri Nets to Model Dynamical Biological Systems -- 1.2 Resilience Properties -- 1.3 Modeling of the Mammalian Circadian Clock -- 1.4 Our Contribution -- 1.5 Outline of the Paper -- 2 Logical Characterization of Circadian Clock Model -- 2.1 Circadian Clock Model -- 2.2 Translation of Gene Regulatory Network to Time Petri Net -- 3 Resilience of Biological Oscillatory Systems -- 3.1 Property Specification -- 3.2 Properties with Observers -- 4 Contribution and Future Work -- References -- Parameter Synthesis by Parallel Coloured CTL Model Checking -- 1 Introduction -- 2 Parallel Parameter Synthesis Algorithm -- 3 Experimental Evaluation -- 4 Conclusions -- References -- Analysing Cell Line Specific EGFR Signalling via Optimized Automata Based Model Checking -- 1 Introduction -- 2 Background -- 3 Methods -- 4 EGFR Signalling Pathway Study -- 4.1 Model Building -- 4.2 Results -- 5 Conclusion -- References -- Short Papers -- OPINION PAPER Evolutionary Constraint-Based Formulation Requires New Bi-level Solving Techniques -- References -- SBMLDock: Docker Driven Systems Biology Tool Development and Usage -- Abstract -- 1 Introduction -- 2 SBMLDock -- 3 Conclusion -- Acknowledgement -- References -- Author Index.
• Sommario/riassunto: This book constitutes the refereed proceedings of the 13th International Conference on Computational Methods in Systems Biology, CMSB 2015, held in Nantes, France, in September 2015. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 43 full and 4 short paper submissions. The papers cover a wide range of topics in the analysis of biological systems, networks and data such as model checking, stochastic analysis, hybrid systems, circadian clock, time series data, logic programming, and constraints solving ranging from intercellular to multiscale.