Martin Schmidt's research while affiliated with Park University and other places

Publications (33)

Article
This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the syste...
Article
This paper describes an adaptive computational intelligence system for learning trading rules. The trading rules are represented using a fuzzy logic rule base, and using an artificial evolutionary process the system learns to form rules that can perform well in dynamic market conditions. A comprehensive analysis of the results of applying the syste...
Chapter
This chapter describes a computational intelligence system for portfolio management and provides a comparison of the relative performance of portfolios of managed by the system using stocks selected from the ASX (Australian Stock Exchange). The core of the system is the development of trading rules to guide portfolio management. The rules the syste...
Conference Paper
Full-text available
This paper describes an adaptive computational intelligence system for learning trading rules used in equity market trading. The rules are represented using fuzzy logic, an evolutionary process facilitates the learning process. By controlling the evolutionary process and through selection of training data the trading rules are adapted to market con...
Conference Paper
The use of memory in coevolutionary systems is considered an important mechanism to counter the Red Queen effect. Our research involves incorporating a memory population that the coevolving populations compete against to obtain a fitness that is influenced by past generations. This long term fitness then allows the population to have continuous lea...
Chapter
This chapter contains a general discussion on the prediction and optimization issues present in dynamic environments, and explains the ideas behind Adaptive Business Intelligence. The chapter also presents three diverse case studies. The first deals with pollution control, the second one with ship navigation, and the third one with car distribution...
Book
Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence includes elements of data mining, predic...
Chapter
We present a description and initial results of a computer code that coevolves Fuzzy Logic rules to play a two-sided zero-sum competitive game. It is based on the TEMPO Military Planning Game that has been used to teach resource allocation to over 20,000 students over the past 40 years. No feasible algorithm for optimal play is known. The coevolved...
Article
Full-text available
We present a description and initial results of a computer code that coevolves fuzzy logic rules to play a two-sided zero-sum competitive game. It is based on the TEMPO Military Planning Game that has been used to teach resource allocation to over 20 000 students over the past 40 years. No feasible algorithm for optimal play is known. The coevolved...
Article
Full-text available
We present a description and initial results of a computer code that coevolves fuzzy logic rules to play a two-sided zero-sum competitive game. It is based on the TEMPO Military Planning Game that has been used to teach resource allocation to over 20 000 students over the past 40 years. No feasible algorithm for optimal play is known. The coevolved...
Article
Full-text available
We present a description and initial results of a com puter code that coevolves Fuzzy Logic rules to play a two-sided zero-sum competitive game. It is based on the TEMPO Military Planning Game that has been used to teach resource allocation to over 20,000 students over the past 40 years. No feasible algorithm for optimal play is known. The coevolve...
Article
The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a non-linear parameter optimisation problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving a design of a scalable test suite of constrained optimi...
Chapter
Full-text available
Evolutionary computation techniques have received a lot of attention regarding their potential as optimization techniques for complex numerical functions. However, they have not produced a significant breakthrough in the area of nonlinear programming due to the fact that they have not addressed the issue of constraints in a systematic way. Only dur...
Article
Full-text available
The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimization problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving the design of a scalable test suite of constrained optim...
Conference Paper
Experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimisation problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving a design of a scalable test suite of constrained optimisatio...
Article
The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimization problem remains an open question. It seems that the most promising approach at this stage of research is experimental# involving a design of a scalable test suite of constrained optimiz...
Article
We will compare the performance of a Genetic Algorithm and Simulated Annealing on instances of difficult real-life Time-Tabling Problems. We will further explain how the performance can be increased significantly by applying a general and very effective genotype-to-phenotype decoding. Furthermore, we will contrast the performance of Lamarckian Lear...
Article
This paper focuses on the issue of evaluation of constraints handling methods, as the advantages and disadvantages of various methods are not well understood. The general way of dealing with constraints -- whatever the optimization method -- is by penalizing infeasible points. However, there are no guidelines on designing penalty functions. Some su...
Conference Paper
Full-text available
The experimental results reported in many papers suggest that making an appropriate a priori choice of an evolutionary method for a nonlinear parameter optimization problem remains an open question. It seems that the most promising approach at this stage of research is experimental, involving a design of a scalable test suite of constrained optimiz...
Article
Games provide the perfect test bed for measuring the effectiveness of computer generated strategies in a competitive and fun environment. Over the years many different games have been tackled by researchers of computational intelligence with the purpose of creating an intelligent computer player that can challenge human players. In this paper the a...

Citations

... Once the artificial neural network (ANN) structure is determined, information can be processed. Major concepts related to processing are inputs, outputs, weights, summation and transfer functions, learning, training the network, testing etc. (Chen, 1996;Chester, 1992;Efraim, 1995). ...
... The spatial grids can be split into a number of domains that are simulated by different groups Figure 6.11: Material temperature at x=0.25cm for Graziani crooked pipe problem of processors. Spectral properties use a 30 frequency group model interpolated for the thermodynamic properties of the medium that is detailed by Kumbera [33]. The coefficients of specific heats at constant volume are determined by tables reported by ...
... The target populations of this study were the town households, all Employees of Town Water Service Provider Office and Town Water Board of Director. In order to determine the sample size from the large target population of households used the following formula:-If N is greater than 10,000 (N > 10,000) using the formula of:n = 2 2 d pq Z .... (Kothari, 2004) Where, n= Desired sample size N= Population size Z = the standard normal variable at the required confidence level or Z statistic (93 %) P= Estimated characteristics of target population q =1-p, non estimated characteristics of the target population d = Level of statistical significance or margin of error (7%) ...
... The data type specifies the performance measurement data type, which can be either int or double (Listing 4, line 44,48). The higher is better key defines whether a higher or a lower value of this metric is better for this use case, and is of type Boolean (Listing 4, line 45,49). The reference value key specifies a reference value for the calculation of the Hypervolume, which needs to be of the same type as specified in data type (Listing 4, line 46,50). ...
... Further, organizations mainly employ it for tactical purposes; reducing costs or increasing operational efficiency is not the main focus of BI and BA; rather, the main focus is on augmenting effectiveness and developing competitive advantages. Therefore, the tools through which management influences an organization's BI and BA competencies are varied of those for developing competencies with other organization systems (Gbosbal & Kim, 1986;Orlikowski, 2000;Lönnqvist & Puhakka, 2006;Michalewicz et al., 2006;Williams et al., 2010;Howson et al., 2018;Sun et al., 2018;Niu et al., 2021). ...
... Historically, constraint satisfaction or constraint handling has been approached from many angles within ec. One approach is concerned with optimisation in continuous spaces under constraints that are often given as equalities or inequalities ( [66], [47], [46], [45], [51], [50], [48]). Another approach focuses on discrete spaces and combinatorial problems that are either formulated as optimisation under constraints, or as pure constraint satisfaction problems. ...
... This concept can also serve to preserve currently unfit individuals with favourable behaviour for later generations when the opponent changes their playing strategy. The mechanism of moving individuals between both short-term and long-term memory was managed later to emulate the psychology of human memory [6]. Moreover, some researchers considered a more precise model of the human brain to add another type of memory (Ultra Short-Term Memory) to the existing two [76]. ...
... Eine weitere Möglichkeit besteht in der Verwendung metaheuristischen Suchverfahren, wie genetischen Algorithmen, die sich aufgrund ihrer hohen Flexibilität besonders für komplexe Parameteroptimierungsaufgaben eignen. Speziell bei stationären Betriebszuständen haben sich derartige Verfahren bewährt [4,5]. Ziel des Beitrages ist die vergleichende Analyse von Optimierungsverfahren für die Parameteridentifikation anhand eines Modells eines Turboverdichters. ...
... In the non-stationary environment, the goal consists in tracking the optimum positions during the optimization process. The problems which are formulated as DOPs, are found in different areas of human activity such as path planning [4,5], pollution control [6], searching for survivors with unmanned aerial vehicles (drones) [7], and others. The development of novel approaches for DOPs relies on well-established benchmarks, namely the classical Moving Peaks Benchmark (MPB) [8], Generalized Dynamic Benchmark Generator (GDBG) [9], or the recently proposed Generalized Moving Peaks Benchmark (GMPB) [10,11] and the Deterministic Distortion and Rotation Benchmark (DDRB) [12]. ...
... If a series of individuals occupy the same minimum-rank level, rank values of each individual are summed up, and the individuals are ordered in terms of the resulting values. Additionally, a simple approach is used to preserve diversity: if the fitness value of a new offspring already exists in the population, it is not inserted into the new population [30]. ...