Game Theory

The Special Issue “Game Theory” of the journal Mathematics provides a collection of papers that represent modern trends in mathematical game theory and its applications. The works address the problem of constructing and implementation of solution concepts based on classical optimality principles in different classes of games. In the case of non-cooperative behavior of players, the Nash equilibrium as a basic optimality principle is considered in both static and dynamic game settings. In the case of cooperative behavior of players, the situation is more complicated. As is seen from presented papers, the direct use of cooperative optimality principles in dynamic and differential games may bring time or subgame inconsistency of a solution which makes the cooperative schemes unsustainable. The notion of time or subgame consistency is crucial to the success of cooperation in a dynamic framework. In the works devoted to dynamic or differential games, this problem is analyzed and the special regularization procedures proposed to achieve time or subgame consistency of cooperative solutions. Among others, special attention in the presented book is paid to the construction of characteristic functions which determine the power of coalitions in games. The book contains many multi-disciplinary works applied to economic and environmental applications in a coherent manner

Preference Learning

This report documents the program and the outcomes of Dagstuhl Seminar 14101 “Preference Learning”. Preferences have recently received considerable attention in disciplines such as machine learning, knowledge discovery, information retrieval, statistics, social choice theory, multiple criteria decision making, decision under risk and uncertainty, operations research, and others. The motivation for this seminar was to showcase recent progress in these different areas with the goal of working towards a common basis of understanding, which should help to facilitate future synergies

An overview of decision table literature 1982-1995.

This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.

Rough set and rule-based multicriteria decision aiding

The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA). DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems

A Review of Bankruptcy Prediction Studies: 1930-Present

One of the most well-known bankruptcy prediction models was developed by Altman [1968] using multivariate discriminant analysis. Since Altman\u27s model, a multitude of bankruptcy prediction models have flooded the literature. The primary goal of this paper is to summarize and analyze existing research on bankruptcy prediction studies in order to facilitate more productive future research in this area. This paper traces the literature on bankruptcy prediction from the 1930\u27s, when studies focused on the use of simple ratio analysis to predict future bankruptcy, to present. The authors discuss how bankruptcy prediction studies have evolved, highlighting the different methods, number and variety of factors, and specific uses of models. Analysis of 165 bankruptcy prediction studies published from 1965 to present reveals trends in model development. For example, discriminant analysis was the primary method used to develop models in the 1960\u27s and 1970\u27s. Investigation of model type by decade shows that the primary method began to shift to logit analysis and neural networks in the 1980\u27s and 1990\u27s. The number of factors utilized in models is also analyzed by decade, showing that the average has varied over time but remains around 10 overall. Analysis of accuracy of the models suggests that multivariate discriminant analysis and neural networks are the most promising methods for bankruptcy prediction models. The findings also suggest that higher model accuracy is not guaranteed with a greater number of factors. Some models with two factors are just as capable of accurate prediction as models with 21 factors

Deep Learning Techniques for Music Generation -- A Survey

This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate musical content. We propose a methodology based on five dimensions for our analysis: Objective - What musical content is to be generated? Examples are: melody, polyphony, accompaniment or counterpoint. - For what destination and for what use? To be performed by a human(s) (in the case of a musical score), or by a machine (in the case of an audio file). Representation - What are the concepts to be manipulated? Examples are: waveform, spectrogram, note, chord, meter and beat. - What format is to be used? Examples are: MIDI, piano roll or text. - How will the representation be encoded? Examples are: scalar, one-hot or many-hot. Architecture - What type(s) of deep neural network is (are) to be used? Examples are: feedforward network, recurrent network, autoencoder or generative adversarial networks. Challenge - What are the limitations and open challenges? Examples are: variability, interactivity and creativity. Strategy - How do we model and control the process of generation? Examples are: single-step feedforward, iterative feedforward, sampling or input manipulation. For each dimension, we conduct a comparative analysis of various models and techniques and we propose some tentative multidimensional typology. This typology is bottom-up, based on the analysis of many existing deep-learning based systems for music generation selected from the relevant literature. These systems are described and are used to exemplify the various choices of objective, representation, architecture, challenge and strategy. The last section includes some discussion and some prospects.Comment: 209 pages. This paper is a simplified version of the book: J.-P. Briot, G. Hadjeres and F.-D. Pachet, Deep Learning Techniques for Music Generation, Computational Synthesis and Creative Systems, Springer, 201

A new approach of top-down induction of decision trees for knowledge discovery

Top-down induction of decision trees is the most popular technique for classification in the field of data mining and knowledge discovery. Quinlan developed the basic induction algorithm of decision trees, ID3 (1984), and extended to C4.5 (1993). There is a lot of research work for dealing with a single attribute decision-making node (so-called the first-order decision) of decision trees. Murphy and Pazzani (1991) addressed about multiple-attribute conditions at decision-making nodes. They show that higher order decision-making generates smaller decision trees and better accuracy. However, there always exist NP-complete combinations of multiple-attribute decision-makings.;We develop a new algorithm of second-order decision-tree inductions (SODI) for nominal attributes. The induction rules of first-order decision trees are combined by \u27AND\u27 logic only, but those of SODI consist of \u27AND\u27, \u27OR\u27, and \u27OTHERWISE\u27 logics. It generates more accurate results and smaller decision trees than any first-order decision tree inductions.;Quinlan used information gains via VC-dimension (Vapnik-Chevonenkis; Vapnik, 1995) for clustering the experimental values for each numerical attribute. However, many researchers have discovered the weakness of the use of VC-dim analysis. Bennett (1997) sophistically applies support vector machines (SVM) to decision tree induction. We suggest a heuristic algorithm (SVMM; SVM for Multi-category) that combines a TDIDT scheme with SVM. In this thesis it will be also addressed how to solve multiclass classification problems.;Our final goal for this thesis is IDSS (Induction of Decision Trees using SODI and SVMM). We will address how to combine SODI and SVMM for the construction of top-down induction of decision trees in order to minimize the generalized penalty cost

2000 USCID international conference

Presented at the 2000 USCID international conference, Challenges facing irrigation and drainage in the new millennium on June 20-24 in Fort Collins, Colorado.Includes bibliographical references.Sponsored by U.S. Committee on Irrigation and Drainage.Multicriteria strategic planning for rehabilitation of the Wind River Irrigation Project, Wyoming -- Environmental management plan for the Irrigation Improvement Project (IIP) - Tajan Subproject -- Organizational requisites of successful irrigation system rehabilitation: cases from Nepal -- Verification-based planning for modernizing irrigation systems -- Policy reforms for sustainable irrigation management in Indonesia -- Bench terracing - a cost effective alternative to traditional irrigation in the Philippines -- GIS-based management system for irrigation districts -- Capacity building for the practice of irrigated agriculture -- Planning of modern irrigation systems integrated with human settlement for enhanced reuse of water -- Drainage in the Aral Sea Basin: past and future -- Impacts and solutions to urbanization on agricultural water resources -- Improving subsurface drainage design and management to reduce salt loads from irrigation areas in southeastern Australia -- Evaluation and update of drainage water management options on the westside San Joaquin Valley, California -- Simulation studies on use of saline water for irrigation in a semi-arid environment -- Hydrodynamic modeling to optimize irrigation efficiency -- Planning to meet future water needs -- Tracing the history of the development and management of two irrigations systems in the Terai of Nepal -- Secondary water supply management for irrigation districts and canal companies -- Role of canal automation and farmer's participation in managing water scarcity: a case study from Orissa, India -- PIM: a reality in Asia? -- Private group irrigation projects in Manitoba: Central Manitoba Resource Management Ltd. - a case study -- Evaluation of dielectric soil moisture sensors for irrigation scheduling on farms -- Sensitivity of micro irrigation emitters to plugging using treated municipal wastewaters -- NCWCD irrigation scheduling program - converting to a web-based accessible program -- On-farm activities to promote irrigation scheduling - the South Kansas Irrigation Management Project

Irrigation and drainage in the new millennium

Presented at the 2000 USCID international conference, Challenges facing irrigation and drainage in the new millennium on June 20-24 in Fort Collins, Colorado.Irrigation scheduling has been promoted as management tool to minimize irrigation water application, however, few irrigators regularly followed any rigorous scheduling methodology. Kansas State University Research and Extension in conjunction with an irrigation association, Water PACK, began a long-term project to promote ET based irrigation scheduling and other management technology. Area irrigators serve as the focal point of the project and over time have been asked to assume responsibility of scheduling the project fields. A long-term commitment and on-farm activities such as variable water application tests and center pivot uniformity tests seems to have generated confidence and acceptance of ET-based irrigation scheduling

Irrigation and drainage in the new millennium

Presented at the 2000 USCID international conference, Challenges facing irrigation and drainage in the new millennium on June 20-24 in Fort Collins, Colorado.Includes bibliographical references.In 1998, eight irrigation districts in the Lower Rio Grande Valley of Texas initiated efforts to develop GIS-based District Management Systems (DMS). This paper provides a description of GIS (geographical information system) as applied to irrigation districts, its potential for improving the day-to-day management of districts, and the progress and difficulties encountered by the 8 districts in GIS mapping and implementation. Examples of how districts are using GIS are given, along with the value and use of the DMS in a regional water planning project