Multiagent cooperation for solving global optimization problems: an extendible framework with example cooperation strategies

This paper proposes the use of multiagent cooperation for solving global optimization problems through the introduction of a new multiagent environment, MANGO. The strength of the environment lays in itsflexible structure based on communicating software agents that attempt to solve a problem cooperatively. This structure allows the execution of a wide range of global optimization algorithms described as a set of interacting operations. At one extreme, MANGO welcomes an individual non-cooperating agent, which is basically the traditional way of solving a global optimization problem. At the other extreme, autonomous agents existing in the environment cooperate as they see fit during run time. We explain the development and communication tools provided in the environment as well as examples of agent realizations and cooperation scenarios. We also show how the multiagent structure is more effective than having a single nonlinear optimization algorithm with randomly selected initial points

Implementing system-wide risk stratification approaches: a review of critical success and failure factors

An Evidence Check rapid review brokered by the Sax Institute for the NSW Agency for Clinical Innovatio

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Good practice guide

Summary with good practices from the Interreg ITRACT project on smart mobility in rural areas

Net.Sense

Net.sense will server as a proof-of-concept of a new type of network management system, using biological models and statistical principles to address scalability, predictability, and reliability issues associated with managing the highly complex computer systems that we as a society have come to depend on

CoMMA Corporate Memory Management through Agents Corporate Memory Management through Agents: The CoMMA project final report

This document is the final report of the CoMMA project. It gives an overview of the different search activities that have been achieved through the project. First, a description of the general requirements is proposed through the definition of two scenarios. Then it shows the different technical aspects of the projects and the solution that has been proposed and implemented

Development of a Multi-Objective Optimization Capability for Heterogeneous Light Water Reactor Fuel Assemblies

As pressure grows on developed nations to move away from fossil fuel-based energy sources, so does the potential for nuclear energy to make its resurgence. However, the complex nature of the design process in nuclear engineering and a regulatory culture of ever-increasing safety standards create unique challenges to the nuclear industry. As in many engineering disciplines, the question is one of trade-offs between safety, performance, cost, and time required to develop the design from paper to real life operation. The possibilities facing a designer are virtually unlimited, with fuel choice, layout and operating conditions just three of the many categories which interact with one another in a highly non-linear manner, making it difficult to quantitatively define these trade-offs. Deciding upon an ‘optimal’ design is therefore traditionally done through expert judgement and an iterative design process. Mathematical optimization methods offer a more formal way to optimize designs by employing algorithms to explore the myriad of possibilities in a methodical manner which can yield increased performance over expert designs. In this thesis, an extensive review of the literature revealed gaps which present opportunities for novel research. Two new algorithms are created with the ability to solve optimization problems with multiple objectives simultaneously without requiring weighting or bias from the designer. They are then applied to a series of problems drawn from both the literature and real world designs. The results demonstrate the algorithms’ effectiveness and robustness as well as their ability to handle complex multi-physics problems with reasonably low computational requirements. This research offers an original and effective tool for performing optimization on nuclear fuel assembly design problems and has advanced the state of the art in both multi-objective optimization and its application to the nuclear engineering industry