Ensemble decision systems for general video game playing

Ensemble Decision Systems offer a unique form of decision making that allows a collection of algorithms to reason together about a problem. Each individual algorithm has its own inherent strengths and weaknesses, and often it is difficult to overcome the weaknesses while retaining the strengths. Instead of altering the properties of the algorithm, the Ensemble Decision System augments the performance with other algorithms that have complementing strengths. This work outlines different options for building an Ensemble Decision System as well as providing analysis on its performance compared to the individual components of the system with interesting results, showing an increase in the generality of the algorithms without significantly impeding performance.Comment: 8 Pages, Accepted at COG201

A Model for an Intelligent Support Decision System in Aquaculture

The paper purpose an intelligent software system agents–based to support decision in aquculture and the approach of fish diagnosis with informatics methods, techniques and solutions. A major purpose is to develop new methods and techniques for quick fish diagnosis, treatment and prophyilaxis at infectious and parasite-based known disorders, that may occur at fishes raised in high density in intensive raising systems. But, the goal of this paper is to presents a model of an intelligent agents-based diagnosis method will be developed for a support decision system.support decision system, diagnosis, multi-agent system, fish diseases

A Multiple Criteria Decision System to Improve Performance of Federal Conservation Programs

The Environmental Quality Incentives Program and other voluntary Federal conservation programs follow a similar approach for enrollment. Consistent with the legislation, agency personnel identify eligibility criteria, suitable conservation practices, and a process to score, rank, and select applications for funding. Our research outlines a formal multiple criteria decision analysis system that is broadly applicable to current Federal conservation programs to score, rank, and enroll applications, and distribute program funds. Then, we apply the decision system to Indiana’s EQIP program using data from 2005. The incorporation of GLEAMS model improved our estimates of water quality impacts by reintroducing the spatial heterogeneity.Multiple Criteria Decision Analysis, Federal Conservation Programs, Environmental Quality Incentives Program, GLEAMS, Environmental Economics and Policy, Research Methods/ Statistical Methods,

Decision system based on neural networks to optimize the energy efficiency of a petrochemical plant

The energy efficiency of industrial plants is an important issue in any type of business but particularly in the chemical industry. Not only is it important in order to reduce costs, but also it is necessary even more as a means of reducing the amount of fuel that gets wasted, thereby improving productivity, ensuring better product quality, and generally increasing profits. This article describes a decision system developed for optimizing the energy efficiency of a petrochemical plant. The system has been developed after a data mining process of the parameters registered in the past. The designed system carries out an optimization process of the energy efficiency of the plant based on a combined algorithm that uses the following for obtaining a solution: On the one hand, the energy efficiency of the operation points occurred in the past and, on the other hand, a module of two neural networks to obtain new interpolated operation points. Besides, the work includes a previous discriminant analysis of the variables of the plant in order to select the parameters most important in the plant and to study the behavior of the energy efficiency index. This study also helped ensure an optimal training of the neural networks. The robustness of the system as well as its satisfactory results in the testing process (an average rise in the energy efficiency of around 7%, reaching, in some cases, up to 45%) have encouraged a consulting company (ALIATIS) to implement and to integrate the decision system as a pilot software in an SCADA

INVESTMENT DECISIONS IN A FIRM AS THE PART OF BUSINESS FINANCIAL DECISION SYSTEM

While the tools and techniques covered in this paper are discussed anddemonstrated in details, the user must not be tempted to view them as the ends in themselves.It’s simply not enough to master the techniques alone! Financial and economic analysis isboth an analytical and judgment process which helps answering questions that have beencarefully posed in management context. The process is at its best when the analyst’s effortsare focused primarily on the structuring the issue and its context, and only secondary on thedata manipulation.Selecting the appropriate tools from the financial decisions is clearly an important part of theanalytical task. Yet, experience has shown again and again that developing a properperspective for the problem or issue is just as important as the choice of the tools themselves.Apart from the providing specific numerical answers the solutions to financial problemsand issue depends significantly on the points of view of the parties involved on the relativeimportance of the issue, and the nature and reliability of the information available.strategic perspective, decisional framework, components of analysis, economic analysismethods.

Study protocol: developing a decision system for inclusive housing: applying a systematic, mixed-method quasi-experimental design

Background Identifying the housing preferences of people with complex disabilities is a much needed, but under-developed area of practice and scholarship. Despite the recognition that housing is a social determinant of health and quality of life, there is an absence of empirical methodologies that can practically and systematically involve consumers in this complex service delivery and housing design market. A rigorous process for making effective and consistent development decisions is needed to ensure resources are used effectively and the needs of consumers with complex disability are properly met. Methods/Design This 3-year project aims to identify how the public and private housing market in Australia can better respond to the needs of people with complex disabilities whilst simultaneously achieving key corporate objectives. First, using the Customer Relationship Management framework, qualitative (Nominal Group Technique) and quantitative (Discrete Choice Experiment) methods will be used to quantify the housing preferences of consumers and their carers. A systematic mixed-method, quasi-experimental design will then be used to quantify the development priorities of other key stakeholders (e.g., architects, developers, Government housing services etc.) in relation to inclusive housing for people with complex disabilities. Stakeholders randomly assigned to Group 1 (experimental group) will participate in a series of focus groups employing Analytical Hierarchical Process (AHP) methodology. Stakeholders randomly assigned to Group 2 (control group) will participate in focus groups employing existing decision making processes to inclusive housing development (e.g., Risk, Opportunity, Cost, Benefit considerations). Using comparative stakeholder analysis, this research design will enable the AHP methodology (a proposed tool to guide inclusive housing development decisions) to be tested. Discussion It is anticipated that the findings of this study will enable stakeholders to incorporate consumer housing preferences into commercial decisions. Housing designers and developers will benefit from the creation of a parsimonious set of consumer-led housing preferences by which to make informed investments in future housing and contribute to future housing policy. The research design has not been applied in the Australian research context or elsewhere, and will provide a much needed blueprint for market investment to develop viable, consumer directed inclusive housing options for people with complex disability