Evolutionary Computation

This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Path planning for mobile robots in the real world: handling multiple objectives, hierarchical structures and partial information

Autonomous robots in real-world environments face a number of challenges even to accomplish apparently simple tasks like moving to a given location. We present four realistic scenarios in which robot navigation takes into account partial information, hierarchical structures, and multiple objectives. We start by discussing navigation in indoor environments shared with people, where routes are characterized by effort, risk, and social impact. Next, we improve navigation by computing optimal trajectories and implementing human-friendly local navigation behaviors. Finally, we move to outdoor environments, where robots rely on uncertain traversability estimations and need to account for the risk of getting stuck or having to change route

Evolutionary design assistants for architecture

In its parallel pursuit of an increased competitivity for design offices and more pleasurable and easier workflows for designers, artificial design intelligence is a technical, intellectual, and political challenge. While human-machine cooperation has become commonplace through Computer Aided Design (CAD) tools, a more improved collaboration and better support appear possible only through an endeavor into a kind of artificial design intelligence, which is more sensitive to the human perception of affairs. Considered as part of the broader Computational Design studies, the research program of this quest can be called Artificial / Autonomous / Automated Design (AD). The current available level of Artificial Intelligence (AI) for design is limited and a viable aim for current AD would be to develop design assistants that are capable of producing drafts for various design tasks. Thus, the overall aim of this thesis is the development of approaches, techniques, and tools towards artificial design assistants that offer a capability for generating drafts for sub-tasks within design processes. The main technology explored for this aim is Evolutionary Computation (EC), and the target design domain is architecture. The two connected research questions of the study concern, first, the investigation of the ways to develop an architectural design assistant, and secondly, the utilization of EC for the development of such assistants. While developing approaches, techniques, and computational tools for such an assistant, the study also carries out a broad theoretical investigation into the main problems, challenges, and requirements towards such assistants on a rather overall level. Therefore, the research is shaped as a parallel investigation of three main threads interwoven along several levels, moving from a more general level to specific applications. The three research threads comprise, first, theoretical discussions and speculations with regard to both existing literature and the proposals and applications of the thesis; secondly, proposals for descriptive and prescriptive models, mappings, summary illustrations, task structures, decomposition schemes, and integratory frameworks; and finally, experimental applications of these proposals. This tripartite progression allows an evaluation of each proposal both conceptually and practically; thereby, enabling a progressive improvement of the understanding regarding the research question, while producing concrete outputs on the way. Besides theoretical and interpretative examinations, the thesis investigates its subject through a set of practical and speculative proposals, which function as both research instruments and the outputs of the study. The first main output of the study is the “design_proxy” approach (d_p), which is an integrated approach for draft making design assistants. It is an outcome of both theoretical examinations and experimental applications, and proposes an integration of, (1) flexible and relaxed task definitions and representations (instead of strict formalisms), (2) intuitive interfaces that make use of usual design media, (3) evaluation of solution proposals through their similarity to given examples, and (4) a dynamic evolutionary approach for solution generation. The design_proxy approach may be useful for AD researchers that aim at developing practical design assistants, as has been examined and demonstrated with the two applications, i.e., design_proxy.graphics and design_proxy.layout. The second main output, the “Interleaved Evolutionary Algorithm” (IEA, or Interleaved EA) is a novel evolutionary algorithm proposed and used as the underlying generative mechanism of design_proxybased design assistants. The Interleaved EA is a dynamic, adaptive, and multi-objective EA, in which one of the objectives leads the evolution until its fitness progression stagnates; in the sense that the settings and fitness values of this objective is used for most evolutionary decisions. In this way, the Interleaved EA enables the use of different settings and operators for each of the objectives within an overall task, which would be the same for all objectives in a regular multi-objective EA. This property gives the algorithm a modular structure, which offers an improvable method for the utilization of domain-specific knowledge for each sub-task, i.e., objective. The Interleaved EA can be used by Evolutionary Computation (EC) researchers and by practitioners who employ EC for their tasks. As a third main output, the “Architectural Stem Cells Framework” is a conceptual framework for architectural design assistants. It proposes a dynamic and multi-layered method for combining a set of design assistants for larger tasks in architectural design. The first component of the framework is a layer-based, parallel task decomposition approach, which aims at obtaining a dynamic parallelization of sub-tasks within a more complicated problem. The second component of the framework is a conception for the development mechanisms for building drafts, i.e., Architectural Stem Cells (ASC). An ASC can be conceived as a semantically marked geometric structure, which contains the information that specifies the possibilities and constraints for how an abstract building may develop from an undetailed stage to a fully developed building draft. ASCs are required for re-integrating the separated task layers of an architectural problem through solution-based development. The ASC Framework brings together many of the ideas of this thesis for a practical research agenda and it is presented to the AD researchers in architecture. Finally, the “design_proxy.layout” (d_p.layout) is an architectural layout design assistant based on the design_proxy approach and the IEA. The system uses a relaxed problem definition (producing draft layouts) and a flexible layout representation that permits the overlapping of design units and boundaries. User interaction with the system is carried out through intuitive 2D graphics and the functional evaluations are performed by measuring the similarity of a proposal to existing layouts. Functioning in an integrated manner, these properties make the system a practicable and enjoying design assistant, which was demonstrated through two workshop cases. The d_p.layout is a versatile and robust layout design assistant that can be used by architects in their design processes

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp