共查询到20条相似文献,搜索用时 15 毫秒
1.
Peter Bock 《Annals of Operations Research》1988,16(1):33-52
The classical approach to the acquisition of knowledge in artificial intelligence has been to program the intelligence into the machine in the form of specific rules for the application of the knowledge: expert systems. Unfortunately, the amount of time and resources required to program an expert system with sufficient knowledge for non-trivial problem-solving is prohibitively large. An alternative approach is to allow the machine tolearn the rules based upon trial-and-error interaction with the environment, much as humans do. This will require endowing the machine with a sophisticated set of sensors for the perception of the external world, the ability to generate trial actions based upon this perceived information, and a dynamic evaluation policy to allow it to measure the effectiveness of its trial actions and modify its repertoire accordingly. The principles underlying this paradigm, known ascollective learning systems theory, have already been applied to sophisticated gaming problems, demonstrating robust learning and dynamic adaptivity.The fundamental building block of a collective learning system is thelearning cell, which may be embedded in a massively parallel, hierarchical data communications network. Such a network comprising 100 million learning cells will approach the intelligence capacity of the human cortex. In the not-too-distant future, it may be possible to build a race of robotic slaves to perform a wide variety of tasks in our culture. This goal, while irresistibly attractive, is most certainly fraught with severe social, political, moral, and economic difficulties.This paper was given as an invited talk on the 12th Symposium on Operations Research, University of Passau, September 1987. 相似文献
2.
Recent anthropological studies have demonstrated that low latitude ‘encounter’ foragers exploit their environments in energetically very efficient manners and closely track the environment as it changes. The paper begins to investigate how they manage to do this by proposing a simple decision making and learning rule developed from an evolutionary ecological basis. Having described the mathematical model the paper refers to simulation studies exploring this model which suggest that some of the seemingly complex aspects of hunter gatherer behaviour may result from the use of simple decision making and learning processes. 相似文献
3.
This paper presents a comprehensive review of 196 studies which employ operational research (O.R.) and artificial intelligence (A.I.) techniques in the assessment of bank performance. Several key issues in the literature are highlighted. The paper also points to a number of directions for future research. We first discuss numerous applications of data envelopment analysis which is the most widely applied O.R. technique in the field. Then we discuss applications of other techniques such as neural networks, support vector machines, and multicriteria decision aid that have also been used in recent years, in bank failure prediction studies and the assessment of bank creditworthiness and underperformance. 相似文献
4.
Alina Constantinescu 《Applications of Mathematics》2007,52(4):321-326
In one if his paper Luo transformed the problem of sum-fuzzy rationality into artificial learning procedure and gave an algorithm
which used the learning rule of perception. This paper extends the Luo method for finding a sum-fuzzy implementation of a
choice function and offers an algorithm based on the artificial learning procedure with fixed fraction. We also present a
concrete example which uses this algorithm. 相似文献
5.
Flannery has suggested that the shift from a hunter-gatherer economy to one based upon incipient agriculture requires a gradual rescheduling of the groups' resource acquisition activities. Here, concepts from Artificial Intelligence and Adaptive Systems are used to develop a model of prehistoric hunter-gatherer decision-making in the valley of Oaxaca, Mexico. This decision-making system was then used to answer the following questions:
- 1. 1. Given randomly specified strategies and no initial knowledge of what available rescheduling decisions will improve performance, can the system produce changes that lead to a mix of strategies that correspond to those used by hunter-gatherers in the valley prior to the introduction of incipient agriculture?
- 2. 2. How would the system adjust its' resource acquisition strategies in response to the introduction of techniques for incipient agriculture?
6.
对于单期的投资者而言,无违约风险的固定收益证券被视为无风险资产.这是因为固定收益证券的收益率在投资的初期就能确定.然而在考虑长期的投资时,投资者可以调整资产配置,固定收益证券也将面临再投资的利率波动风险,因此不能再被视为无风险资产.本文在一类特殊的``习惯形成"效用函数的框架下讨论长期资产配置.在一系列为简化问题而作的假设之下,本文推导出了真实利率波动对风险资产配置权重的影响,并且为计算实际长期资产配置的最优比例提供了理论依据和算法. 相似文献
7.
One of the most significant problems in economic domain is the dispose of human preference and choice forecasting. Recently, the economists have focused their researches to use the fuzzy concepts and the artificial learning procedures in the theory of economic choice. This paper extends the work done in this direction and offers a new algorithm for finding the matrix representation of the fuzzy binary relation which describes a preference relation. 相似文献
8.
David L. Paul John C. Butler Keri E. Pearlson Andrew B. Whinston 《Computational & Mathematical Organization Theory》1996,2(4):301-324
A framework for and a computational model of organizational behavior based on an artificial adaptive system (AAS) is presented. An AAS, a modeling approach based on genetic algorithms, enables the modeling of organizational learning and adaptability. This learning can be represented as decisions to allocate resources to the higher performing organizational agents (i.e., individuals, groups, departments, or processes, depending on the level of analysis) critical to the organization's survival in different environments. Adaptability results from the learning function enabling the organizations to change as the environment changes. An AAS models organizational behavior from a micro-unit perspective, where organizational behavior is a function of the aggregate actions and interactions of each of the individual agents of which the organization is composed. An AAS enables organizational decision making in a dynamic environment to be modeled as a satisficing process and not as a maximization process. To demonstrate the feasibility and usefulness of such an approach, a financial trading adaptive system (FTAS) organization is computationally modeled based on the AAS framework. An FTAS is an example of how the learning mechanism in an AAS can be used to allocate resources to critical individuals, processes, functions, or departments within an organization. 相似文献
9.
Victor DeCaria William Layton Michael McLaughlin 《Numerical Methods for Partial Differential Equations》2019,35(3):916-935
Artificial compression methods create nonphysical acoustic waves. Time filters, often used in geophysical fluid dynamics, are shown in this paper to selectively damp these acoustics. We analyze the stability of a two‐step artificial compression method with the Robert–Asselin (RA) time filter, and provide tests delineating the filter's positive effects on both stability and accuracy. 相似文献
10.
Expert systems have recently become popular and are attracting more and more attention. The high quality performance achieved by some systems in areas previously not considered practical for computational solutions has lead to great interest from many different disciplines. Most expert systems use a subset of techniques from the general area of computer science research known as artificial intelligence. However, some expert systems have been developed that incorporate more traditional mathematical modeling techniques. The combination of artificial intelligence techniques and more traditional mathematical techniques has been shown to be quite effective in developing several high quality performance computer software systems. The techniques used in expert systems may be what is needed to bridge the gap between classical operational research modeling and human decision making processes. This paper addresses how expert systems techniques are being used in problem solving and why someone in operational research might want to use them. 相似文献
11.
An incomplete financial market is considered with a risky asset and a bond. The risky asset price is a pure jump process whose dynamics depends on a jump-diffusion stochastic factor describing the activity of other markets, macroeconomics factors or microstructure rules that drive the market. With a stochastic control approach, maximization of the expected utility of terminal wealth is discussed for utility functions of constant relative risk aversion type. Under suitable assumptions, closed form solutions for the value functions and for the optimal strategy are provided and verification results are discussed. Moreover, the solution to the dual problems associated with the utility maximization problems is derived. 相似文献
12.
Alexei Borodin 《Advances in Mathematics》2011,228(4):201
We construct discrete time Markov chains that preserve the class of Schur processes on partitions and signatures.One application is a simple exact sampling algorithm for qvolume-distributed skew plane partitions with an arbitrary back wall. Another application is a construction of Markov chains on infinite Gelfand–Tsetlin schemes that represent deterministic flows on the space of extreme characters of the infinite-dimensional unitary group. 相似文献
13.
A self‐adaptive intelligence gray prediction model with the optimal fractional order accumulating operator and its application 下载免费PDF全文
The self‐adaptive intelligence gray predictive model (SAIGM) has an alterable‐flexible model structure, and it can build a dynamic structure to fit different external environments by adjusting the parameter values of SAIGM. However, the order number of the raw SAIGM model is not optimal, which is an integer. For this, a new SAIGM model with the fractional order accumulating operator (SAIGM_FO) was proposed in this paper. Specifically, the final restored expression of SAIGM_FO was deduced in detail, and the parameter estimation method of SAIGM_FO was studied. After that, the Particle Swarm Optimization algorithm was used to optimize the order number of SAIGM_FO, and some steps were provided. Finally, the SAIGM_FO model was applied to simulate China's electricity consumption from 2001 to 2008 and forecast it during 2009 to 2015, and the mean relative simulation and prediction percentage errors of the new model were only 0.860% and 2.661%, in comparison with the ones obtained from the raw SAIGM model, the GM(1, 1) model with the optimal fractional order accumulating operator and the GM(1, 1) model, which were (1.201%, 5.321%), (1.356%, 3.324%), and (2.013%, 23.944%), respectively. The findings showed both the simulation and the prediction performance of the proposed SAIGM_FO model were the best among the 4 models. 相似文献
14.
15.
《Applied Mathematical Modelling》2014,38(9-10):2435-2453
A mechatronic approach integrating both passive and active controllers is presented in this study to deal with unwanted noise and vibration produced in an automobile wiper system operation. Wiper system is a flexible structure with high order, nonlinear model that is considered as a multi objective control problem since there is a conflict between its functionality quality in wiping and generated unwanted noise and vibration. A passive control technique using multi body system (MBS) model and finite element analysis (FEA) is introduced to identify the potential of the effectiveness of the physical parameters of wiper blade to give appropriate range to reduce the unwanted noise and vibration in the system. While, the significant contribution of active controller is to deal with uncertainties exerted to system within wiper operation. In passive control stage, natural frequencies of a uni-blade automobile wiper are determined using modal testing. Later, a 3-dimensional model of a wiper blade assembly is developed in multi body system design to investigate the good validation test and agreement of the physical behavior of the system in experiment with finite element analysis. Parametric modification via complex eigenvalue is adopted to predict instability of the wiper blade. In active control level, experimental data collected from the wiper system during its operation. A system identification model named nonlinear auto regressive exogenous Elman neural network (NARXENN) is developed for implying the active controller. A bi-level adaptive-fuzzy controller is brought in whose parameters are tuned simultaneously by a multi objective genetic algorithm (MOGA) to deal with the conflict interests in wiper control problem. 相似文献
16.
Guillermina Jasso 《The Journal of mathematical sociology》2013,37(2-3):219-251
This paper examines the usefulness for theoretical work of the narrative method proposed by Peter Abell. Our assessment proceeds by using the narrative method to perform the two main tasks of theoretical analysis—constructing postulates and deriving predictions. Tb illustrate, we focus on the theory of distributive justice and the more general theory of comparison processes to which it led. The results of our assessment of the usefulness of Abell's narrative method for theoretical work indicate that the narrative method has far wider applicability than Abell has claimed for it. For example, (i) it is useful for all theoretical work in the sociobehavioral sciences, not only for theoretical work based on game theory, (ii) it is useful for analyzing thought‐experiments as well as narrative accounts of actual actions and events, and (iii) the events in the narrative need not be restricted to human actions but can include events not traceable to human agency. We conclude also that Abell's narrative method complements the use of mathematical analysis in theoretical work and that it may be especially valuable for theoretical derivation involving two or more theories jointly. 相似文献
17.
Margaret P. Sinclair 《The Journal of Mathematical Behavior》2005,24(1):89-107
A case study, originally set up to identify and describe some benefits and limitations of using dynamic web-based geometry sketches, provided an opportunity to examine peer interactions in a lab. Since classes were held in a computer lab, teachers and pairs faced the challenges of working and communicating in a lab environment.Research has shown that particular teacher interventions provide motivation for the consideration of new ideas, and help uncover misunderstandings that may interfere with student progress [Towers, J. (1999). In what ways do teachers interventions interact with and occasion the growth of students’ mathematical understanding. Doctoral Dissertation, University of British Columbia, Unpublished]. Examples of student discourse presented here suggest that certain peer interactions act in similar ways—helping propel students towards new understanding. On the other hand, they also show that some peer interactions, although superficially similar to teacher interventions, may hamper student progress. 相似文献
18.
In a recent paper, Stadje analyzed the space-time properties of some storage processes. We give a short probabilistic proof
of these results.
This revised version was published online in June 2006 with corrections to the Cover Date. 相似文献
19.
We explore the use of deep learning hierarchical models for problems in financial prediction and classification. Financial prediction problems – such as those presented in designing and pricing securities, constructing portfolios, and risk management – often involve large data sets with complex data interactions that currently are difficult or impossible to specify in a full economic model. Applying deep learning methods to these problems can produce more useful results than standard methods in finance. In particular, deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
20.
In this paper it is shown, by means of simulation, that interesting time behavior is observed for damaged and overloaded networks, and that adaptive, decentralized intelligence can have a dramatic influence on the overall network performance. The time behavior of nonhierarchical networks is modeled by a system of nonlinear difference equations among global variables, and bistability is shown to exist. Using a simple adaptive control mechanism, it is shown that, depending upon the value of a certain network variable, either limit cycle or steady state behavior results. A few ideas are discussed for applications of nonhierarchical communications to cellular automata and to decision-making systems. 相似文献