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Simula Research Laboratory: by Thinking Constantly about it

When researchers gather around lunch tables, at conferences, or in bars, there are some topics that are more or less compulsory. The discussions are about the ho- less management of the university or the lab where they are working, the lack of funding for important research, politicians’ inability to grasp the potential of a p- ticularly promising ?eld, and the endless series of committees that seem to produce very little progress. It is common to meet excellent researchers claiming that they have almost no time to do research because writing applications, lecturing, and - tending to committee work seem to take most of their time. Very few ever come into a position to do something about it. With Simula we have this chance. We were handed a considerable annual grant and more or less left to ourselves to do whatever we thought would produce the best possible results. We wanted to create a place where researchers could have the time and conditions necessary to re?ect over dif?cult problems, uninterrupted by mundane dif?culties; where doctoral students could be properly supervised and learn the craft of research in a well-organized and professional manner; and where entrepreneurs could ?nd professional support in developing their research-based - plications and innovations.

Simulated Annealing for VLSI Design (The Springer International Series in Engineering and Computer Science #42)

This monograph represents a summary of our work in the last two years in applying the method of simulated annealing to the solution of problems that arise in the physical design of VLSI circuits. Our study is experimental in nature, in that we are con­ cerned with issues such as solution representations, neighborhood structures, cost functions, approximation schemes, and so on, in order to obtain good design results in a reasonable amount of com­ putation time. We hope that our experiences with the techniques we employed, some of which indeed bear certain similarities for different problems, could be useful as hints and guides for other researchers in applying the method to the solution of other prob­ lems. Work reported in this monograph was partially supported by the National Science Foundation under grant MIP 87-03273, by the Semiconductor Research Corporation under contract 87-DP- 109, by a grant from the General Electric Company, and by a grant from the Sandia Laboratories.

Simulated Annealing: Theory and Applications (Mathematics and Its Applications #37)

It isn't that they can't see the solution. It is Approach your problems from the right end and begin with the answers. Then one day, that they can't see the problem. perhaps you will find the final question. O. K. Chesterton. The Scandal of Father 'The Hermit Clad in Crane Feathers' in R. Brown 'The point of a Pin'. van Oulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks or increasingly specialized topics. However, the "tree" of knowledg~ of mathematics and related fields does not grow only by putting forth new branches. It also ·happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the ~d and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addition to this there are such new emerging subdisciplines as "experimental mathematics", "CFD", "completely integrable systems", "chaos, synergetics and large-scale order", which are almost impossible to fit into the existing classification schemes. They draw upon widely different sections of mathematics.

Simulated Evolution and Learning: 9th International Conference, SEAL 2012, Hanoi, Vietnam, December 16-19, 2012, Proceedings (Lecture Notes in Computer Science #7673)

This volume constitutes the proceedings of the 9th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Hanoi, Vietnam, in December 2012. The 50 full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on evolutionary algorithms, theoretical developments, swarm intelligence, data mining, learning methodologies, and real-world applications.

Simulated Evolution and Learning: 8th International Conference, SEAL 2010, Kanpur, India, December 1-4, 2010, Proceedings (Lecture Notes in Computer Science #6457)

Simulated Evolution and Learning: 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, Proceedings (Lecture Notes in Computer Science #8886)

This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.

Simulated Evolution and Learning: 7th International Conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008, Proceedings (Lecture Notes in Computer Science #5361)

This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.

Simulated Evolution and Learning: Second Asia-Pacific Conference on Simulated Evolution and Learning, SEAL'98, Canberra, Australia, November 24-27, 1998 Selected Papers (Lecture Notes in Computer Science #1585)

This volume contains selected papers presented at the Second Asia-Paci c C- ference on Simulated Evolution and Learning (SEAL’98), from 24 to 27 Nov- ber 1998, in Canberra, Australia. SEAL’98 received a total of 92 submissions (67 papers for the regular sessions and 25 for the applications sessions). All papers were reviewed by three independent reviewers. After review, 62 papers were - cepted for oral presentation and 13 for poster presentation. Some of the accepted papers were selected for inclusion in this volume. SEAL’98 also featured a fully refereed special session on Evolutionary Computation in Power Engineering - ganised by Professor Kit Po Wong and Dr Loi Lei Lai. Two of the ve accepted papers are included in this volume. The papers included in these proceedings cover a wide range of topics in simulated evolution and learning, from self-adaptation to dynamic modelling, from reinforcement learning to agent systems, from evolutionary games to e- lutionary economics, and from novel theoretical results to successful applications, among others. SEAL’98 attracted 94 participants from 14 di erent countries, namely A- tralia, Belgium, Brazil, Germany, Iceland, India, Japan, South Korea, New Z- land, Portugal, Sweden, Taiwan, UK and the USA. It had three distinguished international scientists as keynote speakers, giving talks on natural computation (Hans-Paul Schwefel), reinforcement learning (Richard Sutton), and novel m- els in evolutionary design (John Gero). More information about SEAL’98 is still available at http://www.cs.adfa.edu.au/conference/seal98/.

Simulated Evolution and Learning: 11th International Conference, SEAL 2017, Shenzhen, China, November 10–13, 2017, Proceedings (Lecture Notes in Computer Science #10593)

This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.

Simulated Evolution and Learning: 6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006, Proceedings (Lecture Notes in Computer Science #4247)

This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420 submissions.

Simulating Complex Systems by Cellular Automata (Understanding Complex Systems)

Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students, this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on theory and applications, and a smaller part on software. The theory part contains fundamental chapters on how to design and/or apply CA for many different areas. In the applications part a number of representative examples of really using CA in a broad range of disciplines is provided - this part will give the reader a good idea of the real strength of this kind of modeling as well as the incentive to apply CA in their own field of study. Finally, we included a smaller section on software, to highlight the important work that has been done to create high quality problem solving environments that allow to quickly and relatively easily implement a CA model and run simulations, both on the desktop and if needed, on High Performance Computing infrastructures.

Simulating Continuous Fuzzy Systems (Studies in Fuzziness and Soft Computing #188)

1. 1 Introduction This book is written in two major parts. The ?rst part includes the int- ductory chapters consisting of Chapters 1 through 6. In part two, Chapters 7-26, we present the applications. This book continues our research into simulating fuzzy systems. We started with investigating simulating discrete event fuzzy systems ([7],[13],[14]). These systems can usually be described as queuing networks. Items (transactions) arrive at various points in the s- tem and go into a queue waiting for service. The service stations, preceded by a queue, are connected forming a network of queues and service, until the transaction ?nally exits the system. Examples considered included - chine shops, emergency rooms, project networks, bus routes, etc. Analysis of all of these systems depends on parameters like arrival rates and service rates. These parameters are usually estimated from historical data. These estimators are generally point estimators. The point estimators are put into the model to compute system descriptors like mean time an item spends in the system, or the expected number of transactions leaving the system per unit time. We argued that these point estimators contain uncertainty not shown in the calculations. Our estimators of these parameters become fuzzy numbers, constructed by placing a set of con?dence intervals one on top of another. Using fuzzy number parameters in the model makes it into a fuzzy system. The system descriptors we want (time in system, number leaving per unit time) will be fuzzy numbers.

Simulating Conversations for the Prediction of Speech Quality (T-Labs Series in Telecommunication Services)

This book discusses the simulation of conversations through a novel approach of predicting speech quality based on the interactions of two simulated interlocutors. The author describes the setup of a simulation environment that is capable of simulating human dialogue on the speech level. The impact of delay and bursty packet loss on VoIP conversations is investigated and modeled for the use in the simulation. Based on parameters extracted from simulated conversations, the author proposes extensions to the E-model, a parametric model standardized by the International Telecommunications Union, in order to predict the quality of the simulated conversations. The author shows that predictions based on the simulated conversations outperform models that rely on the transmission parameters alone.

Simulating Crowds in Egress Scenarios

This book describes, from a computer science viewpoint the software, methods of simulating and analysing crowds with a particular focus on the effects of panic in emergency situations.The power of modern technology impacts on modern life in multiple ways every day. A variety of scientific models and computational tools have been developed to improve human safety and comfort in built environments. In particular, understanding pedestrian behaviours during egress situations is of considerable importance in such contexts. Moreover, some places are built for large numbers of people (such as train stations and airports and high volume special activities such as sporting events). Simulating Crowds in Egress Scenarios discusses the use of computational crowd simulation to reproduce and evaluate egress performance in specific scenarios. Several case studies are included, evaluating the work and different analyses, and comparisons of simulation data versus data obtained from real-life experiments are given.

Simulating Heterogeneous Crowds with Interactive Behaviors

This book provides a deep understanding of state-of-art methods for simulation of heterogeneous crowds in computer graphics. It will cover different aspects that are necessary to achieve plausible crowd behaviors. The book will be a review of the most recent literature in this field that can help professionals and graduate students interested in this field to get up to date with the latest contributions, and open problems for their possible future research. The chapter contributors are well known researchers and practitioners in the field and they include their latest contributions in the different topics required to achieve believable heterogeneous crowd simulation. Provides crowd simulation methodology to populate virtual environments, for video games or any kind of applications that requires believable multi-agent behavior Presents the latest contributions on crowd simulation, animation, planning, rendering and evaluation with detailed algorithms for implementation purposes Includes perspectives of both academic researchers and industrial practitioners with reference to open source solutions and commercial applications, where appropriate

Simulating Heterogeneous Crowds with Interactive Behaviors

This book provides a deep understanding of state-of-art methods for simulation of heterogeneous crowds in computer graphics. It will cover different aspects that are necessary to achieve plausible crowd behaviors. The book will be a review of the most recent literature in this field that can help professionals and graduate students interested in this field to get up to date with the latest contributions, and open problems for their possible future research. The chapter contributors are well known researchers and practitioners in the field and they include their latest contributions in the different topics required to achieve believable heterogeneous crowd simulation. Provides crowd simulation methodology to populate virtual environments, for video games or any kind of applications that requires believable multi-agent behavior Presents the latest contributions on crowd simulation, animation, planning, rendering and evaluation with detailed algorithms for implementation purposes Includes perspectives of both academic researchers and industrial practitioners with reference to open source solutions and commercial applications, where appropriate

Simulating Humans: Computer Graphics Animation and Control

During the past decade, high-performance computer graphics have found application in an exciting and expanding range of new domains. Among the most dramatic developments has been the incorporation of real-time interactive manipulation and display for human figures. Though actively pursued by several research groups, the problem of providing a synthetic or surrogate human for engineers and designers already familiar with computer-aided design techniques was most comprehensively solved by Norman Badler's computer graphics laboratory at the University of Pennsylvania. The breadth of that effort as well as the details of its methodology and software environment are presented in this volume. The book is intended for human factors engineers interested in understanding how a computer-graphics surrogate human can augment their analyses of designed environments. It will also inform design engineers of the state of the art in human figure modeling, and hence of the human-centered design central to the emergent concept of concurrent engineering. In fulfilling these goals, the book additionally documents for the entire computer graphics community a major research effort in the interactive control of articulated human figures.

Simulating Information Retrieval Test Collections (Synthesis Lectures on Information Concepts, Retrieval, and Services)

Simulated test collections may find application in situations where real datasets cannot easily be accessed due to confidentiality concerns or practical inconvenience. They can potentially support Information Retrieval (IR) experimentation, tuning, validation, performance prediction, and hardware sizing. Naturally, the accuracy and usefulness of results obtained from a simulation depend upon the fidelity and generality of the models which underpin it. The fidelity of emulation of a real corpus is likely to be limited by the requirement that confidential information in the real corpus should not be able to be extracted from the emulated version. We present a range of methods exploring trade-offs between emulation fidelity and degree of preservation of privacy. We present three different simple types of text generator which work at a micro level: Markov models, neural net models, and substitution ciphers. We also describe macro level methods where we can engineer macro properties of a corpus, giving a range of models for each of the salient properties: document length distribution, word frequency distribution (for independent and non-independent cases), word length and textual representation, and corpus growth. We present results of emulating existing corpora and for scaling up corpora by two orders of magnitude. We show that simulated collections generated with relatively simple methods are suitable for some purposes and can be generated very quickly. Indeed it may sometimes be feasible to embed a simple lightweight corpus generator into an indexer for the purpose of efficiency studies. Naturally, a corpus of artificial text cannot support IR experimentation in the absence of a set of compatible queries. We discuss and experiment with published methods for query generation and query log emulation. We present a proof-of-the-pudding study in which we observe the predictive accuracy of efficiency and effectiveness results obtained on emulated versions of TREC corpora. The study includes three open-source retrieval systems and several TREC datasets. There is a trade-off between confidentiality and prediction accuracy and there are interesting interactions between retrieval systems and datasets. Our tentative conclusion is that there are emulation methods which achieve useful prediction accuracy while providing a level of confidentiality adequate for many applications. Many of the methods described here have been implemented in the open source project SynthaCorpus, accessible at: https://bitbucket.org/davidhawking/synthacorpus/

Simulating Interacting Agents and Social Phenomena: The Second World Congress (Agent-Based Social Systems #7)

Agent-based modeling and social simulation have emerged as an interdisciplinary area of social science that includes computational economics, organizational science, social dynamics, and complex systems. This area contributes to enriching our understanding of the fundamental processes of social phenomena caused by complex interactions among agents. Bringing together diverse approaches to social simulation and research agendas, this book presents a unique collection of contributions from the Second World Congress on Social Simulation, held in 2008 at George Mason University in Washington DC, USA. This book in particular includes articles on norms, diffusion, social networks, economy, markets and organizations, computational modeling, and programming environments, providing new hypotheses and theories, new simulation experiments compared with various data sets, and new methods for model design and development. These works emerged from a global and interdisciplinary scientific community of the three regional scientific associations for social simulation: the North American Association for Computational Social and Organizational Science (NAACSOS; now the Computational Social Science Society, CSSS), the European Social Simulation Association (ESSA), and the Pacific Asian Association for Agent-bBased Approach in Social Systems Sciences (PAAA).

Simulating Knowledge Dynamics in Innovation Networks (Understanding Complex Systems)

The competitiveness of firms, regions and countries greatly depends on the generation, dissemination and application of new knowledge. Modern innovation research is challenged by the need to incorporate knowledge generation and dissemination processes into the analysis so as to disentangle the complexity of these dynamic processes. With innovation, however, strong uncertainty, nonlinearities and actor heterogeneity become central factors that are at odds with traditional modeling techniques anchored in equilibrium and homogeneity. This text introduces SKIN (Simulation Knowledge Dynamics in Innovation Networks), an agent-based simulation model that primarily focuses on joint knowledge creation and exchange of knowledge in innovation co‐operations and networks. In this context, knowledge is explicitly modeled and not approximated by, for instance, the level of accumulated R&D investment. The SKIN approach supports applications in different domains ranging from sector-based research activities in knowledge-intensive industries to the activities of international research consortia engaged in basic and applied research. Following a general description of the SKIN model, several applications and modifications are presented. Each chapter introduces in detail the structure of the model, the relevant methodological considerations and the analysis of simulation results, while options for empirically validating the models’ structure and outcomes are also discussed. The book considers the scope of further applications and outlines prospects for the development of joint modeling strategies.

Simulating Nonlinear Circuits with Python Power Electronics: An Open-Source Simulator, Based on Python™

This book provides readers with an in-depth discussion of circuit simulation, combining basic electrical engineering circuit theory with Python programming. It fills an information gap by describing the development of Python Power Electronics, an open-source software for simulating circuits, and demonstrating its use in a sample circuit. Unlike typical books on circuit theory that describe how circuits can be solved mathematically, followed by examples of simulating circuits using specific, commercial software, this book has a different approach and focus. The author begins by describing every aspect of the open-source software, in the context of non-linear power electronic circuits, as a foundation for aspiring or practicing engineers to embark on further development of open source software for different purposes. By demonstrating explicitly the operation of the software through algorithms, this book brings together the fields of electrical engineering and software technology.

Simulating Prehistoric and Ancient Worlds (Computational Social Sciences)

This book presents a unique selection of fully reviewed, extended papers originally presented at the Social Simulation Conference 2014 in Barcelona, Spain. Only papers on the simulation of historical processes have been selected, the aim being to present theories and methods of computer simulation that can be relevant to understanding the past. Applications range from the Paleolithic and the origins of social life up to the Roman Empire and Early Modern societies. Case studies from Europe, America, Africa and Asia have been selected for publication. The extensive introduction offers a thorough review of the computer simulation of social dynamics in past societies as a means of understanding human history. This book will be of great interest to researchers in the social sciences, archaeology, evolutionary anthropology, and social history.

Simulating Science: Computer Simulations as Scientific Instruments (Synthese Library #479)

This book provides a philosophical framework to understand computer simulations as scientific instruments. This is in sharp contrast to existing philosophical approaches on the subject, which have historically understood computer simulations as either formal abstractions or as broadly construed empirical practices. In order to make its case, the volume contains a thorough examination of conventional philosophical approaches as well as their respective limitations. Yet, also, unlike other accounts of computer simulations from the perspective of the philosophy of science, this book incorporates insights from the philosophy of technology and the history of science. Hence, the book offers philosophers of science, technologists and other researchers interested in the topic, a thorough overview of the philosophical issues regarding the design, development and deployment of computer simulations in science and science-based policy making.

Simulating Social Complexity: A Handbook (Understanding Complex Systems)

Social systems are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible and natural language approaches inadequate for relating intricate cause and effect. However, individual- and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems. Simulating Social Complexity examines all aspects of using agent- or individual-based simulation. This approach represents systems as individual elements having each their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes these elements "social" is that they are usefully interpretable as interacting elements of an observed society. In this, the focus is on human society, but can be extended to include social animals or artificial agents where such work enhances our understanding of human society. The phenomena of interest then result (emerge) from the dynamics of the interaction of social actors in an essential way and are usually not easily simplifiable by, for example, considering only representative actors. The introduction of accessible agent-based modelling allows the representation of social complexity in a more natural and direct manner than previous techniques. In particular, it is no longer necessary to distort a model with the introduction of overly strong assumptions simply in order to obtain analytic tractability. This makes agent-based modelling relatively accessible to a range of scientists. The outcomes of such models can be displayed and animated in ways that also make them more interpretable by experts and stakeholders. This handbook is intended to help in the process of maturation of this new field. It brings together, through the collaborative effort of many leading researchers, summaries of the best thinking and practice in this area and constitutes a reference point for standards against which future methodological advances are judged. This book will help those entering into the field to avoid "reinventing the wheel" each time, but it will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introductory, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section of ‘Further Reading’ briefly describing three to eight items that a newcomer might read next.

Simulating Social Complexity: A Handbook (Understanding Complex Systems)

This volume examines all aspects of using agent or individual-based simulation. This approach represents systems as individual elements having their own set of differing states and internal processes. The interactions between elements in the simulation represent interactions in the target systems. What makes this "social" is that it can represent an observed society.Social systems include all those systems where the components have individual agency but also interact with each other. This includes human societies and groups, but also increasingly socio-technical systems where the internet-based devices form the substrate for interaction. These systems are central to our lives, but are among the most complex known. This poses particular problems for those who wish to understand them. The complexity often makes analytic approaches infeasible but, on the other hand, natural language approaches are also inadequate for relating intricate cause and effect. This is why individual and agent-based computational approaches hold out the possibility of new and deeper understanding of such systems.This handbook marks the maturation of this new field. It brings together summaries of the best thinking and practices in this area from leading researchers in the field and constitutes a reference point for standards against which future methodological advances can be judged.This second edition adds new chapters on different modelling purposes and applying software engineering methods to simulation development. Revised existing content will keep the book up-to-date with recent developments. This volume will help those new to the field avoid "reinventing the wheel" each time, and give them a solid and wide grounding in the essential issues. It will also help those already in the field by providing accessible overviews of current thought. The material is divided into four sections: Introduction, Methodology, Mechanisms, and Applications. Each chapter starts with a very brief section called ‘Why read this chapter?’ followed by an abstract, which summarizes the content of the chapter. Each chapter also ends with a section on ‘Further Reading’.Whilst sometimes covering technical aspects, this second edition of Simulating Social Complexity is designed to be accessible to a wide range of researchers, including both those from the social sciences as well as those with a more formal background. It will be of use as a standard reference text in the field and also be suitable for graduate level courses.