THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

An Introduction to MultiAgent Systems.

Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.

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Multiagent systems: a modern approach to distributed artificial intelligence

Microsoft has promoted ASP.NET’s new web services more than almost any other part of the.NET Framework. But despite their efforts, confusion is still widespread about what a web service is and, more importantly, what it’s meant to accomplish. This chapter introduces web services and explains their role in Microsoft’s vision of the programmable web. Along the way, you’ll learn about the open standards plumbing that allows web services to work and removes some of the confusion surrounding technical terms like WSDL (Web Service Description Language), SOAP, and UDDI (universal description, discovery, and integration).

Web Services Architecture

There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by concerns for the environment and also new developments in technologies which enable new modes of operations. This paper surveys the research developments on the Dial-A-Ride Problem (DARP) since 2007. We provide a classification of the problem variants and the solution methodologies, and references to benchmark instances. We also present some application areas for the DARP, discuss some future trends and challenges, and indicate some possible directions for future research.

A survey of dial-a-ride problems: Literature review and recent developments

On the Dial-a-Ride with time windows (DARPTW) customer transportation problem, there is a set of requests from customers to be transported from an origin place to a delivery place through a locations network, under several constraints like the time windows. The problem complexity (NP-Hard) forces the use of heuristics on its resolution. In this context, the application of Genetic Algorithms (GA) on DARPTW was not largely considered, with the exception of a few researches. In this work, under a restrictive scenario, a GA model for the problem was developed based on the adaptation of a generic GA model from literature. Our solution applies data pre-processing techniques to reduce the search space to points that are feasible regarding time windows constraints. Tests show competitive results on Cordeau & Laporte benchmark datasets while improving processing times.

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Application of Genetic Algorithms for the DARPTW Problem

We design a decision-making system bio-inspired in human emotions.Both rational and emotional components operate in every decision as a unique layer.Official data of New York Stock Exchange Market is used.The emotional decision model used can improve the effectiveness of each decision. This work presents an autonomous affective decision-making system devoted to the support of decision-making processes in the stock exchange market domain. The current proposals of intelligent systems and automated platforms to support operations in the stock exchange market use strongly analytical indicators. However, the above represents an important limitation because all decisions made by these proposals must be defined and constantly monitored by human investors. The use of artificial emotions allows the system to configure its own notion of confidence based on the correlation between investment decisions made and the associated emotional reactions. The above allows the system to increase the degree of autonomy in its decisions by providing a mechanism that is more adaptive to changing stock exchange market conditions. In this way, the delegation of decision-making by human investors is promoted. A definition of an artificial emotional decision-making system was implemented and applied to real data of the New York Stock Exchange Market. The results are promising and suggest that using artificial emotions in autonomous decision-making systems can represent an important future research area, improving the effectiveness of each decision.

Decision-making system for stock exchange market using artificial emotions

This work presents the results on applying a genetic approach for solving the Dial-A-Ride Problem (DARP). The problem consists of assigning and scheduling a set of user transport requests to a fleet of available vehicles in the most efficient way according to a given objective function. The literature offers different heuristics for solving DARP, a well known NP-hard problem, which range from traditional insertion and clustering algorithms to soft computing techniques. On the other hand, the approach through Genetic Algorithms (GA) has been experienced in problems of combinatorial optimization. We present our experience and results of a study to develop and test different GAs in the aim of finding an appropriate encoding and configuration, specifically for the DARP problem with time windows.

A Study on Genetic Algorithms for the DARP Problem

The dial-a-ride problem with time windows (DARPTW) is a combinatorial optimization problem related to transportation, in which a set of customers must be picked up from an origin location and they have to be delivered to a destination location. A transportation schedule must be constructed for a set of available vehicles, and several constraints have to be considered, particularly time windows, which define an upper and lower time bound for each customer request in which a vehicle must arrive to perform the service. Because of the complexity of DARPTW, a number of algorithms have been proposed for solving the problem, mainly based on metaheuristics such as Genetic Algorithms and Simulated Annealing. In this work, a different approach for solving DARPTW is proposed, designed, and evaluated: hyperheuristics, which are alternative heuristic methods that operate at a higher abstraction level than metaheuristics, because rather than searching in the problem space directly, they search in a space of low-level heuristics to find the best strategy through which good solutions can be found. Although the proposed hyperheuristic uses simple and easy-to-implement operators, the experimental results demonstrate efficient and competitive performance on DARPTW when compared to other metaheuristics from the literature.

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A Hyperheuristic for the Dial-a-Ride Problem with Time Windows

A higher number of people increasingly uses digital games. This growing interest in games, with different objectives, justifies the investigation of some aspects and concepts involved, such as product quality (game), usability, playability, and user or player experience, topics investigated by the multidisciplinary area called Human–Computer Interaction (HCI). Although the majority of users of these games are children and young people, an increasing number of older adults join technology and use different types of digital games. Several studies establish the increase in learning, socialization and exercise promotion, and cognitive and psychomotor skills improvement, all within the context of active and healthy aging. The objective of this work is to carry out a systematic literature review investigating the player experience of the elderly in digital games. The work allowed answering five research questions that were formulated. The evolution and maturity level of the research area are studied together with the research methods used. The factors that motivate adults to play were also analyzed; what are the recommended technical characteristics for games and some tools and metrics with which games are evaluated for older adults? Research gaps were detected in the area; there are not many specific studies on playability and player experience applied to the older adult, nor are there proven tools and metrics to evaluate them. Particular techniques for assessing and designing games focused on older adults are lacking, and quantitative studies that better identify the factors that affect the playability and experience of older adults in digital games.

https://www.mdpi.com/1424-8220/20/14/3958/pdf

Claudio Cubillos

Papers

Application of Genetic Algorithms for the DARPTW Problem

Decision-making system for stock exchange market using artificial emotions

A Study on Genetic Algorithms for the DARP Problem

A Hyperheuristic for the Dial-a-Ride Problem with Time Windows

Playability and Player Experience in Digital Games for Elderly: A Systematic Literature Review.