AN INTELLIGENT ASSISTANT FOR FINANCIAL HEDGING

Problems in Finance, particularly those involving risk assessment and management, have been slow to yield to expert systems technology for two reasons. First, expert reasoning in such problems is often based on âfirst principles" instead of âsituation-action" rules that characterize most expert systems. Secondly, the knowledge involved, such as that about financial instruments, is constantly changing. This would make it extremely difficult to keep a rule-base accurate. We have developed a representation in the domain of financial hedging that has the following characteristics. First, it allows for reasoning qualitatively based on first principles using the fundamental quantitative valuation models that characterize each instrument. Secondly, it uses object oriented concepts and inheritance to minimize the effort needed to set up the knowledge base and keep it current. Thirdly, it includes a calculus for derivation of qualitative knowledge of "one-dimensional-order", which allows it to solve problems where optimality constraints are qualitative.Information Systems Working Papers Serie

Expert Systems as Applied to Future Space Transportation Syst

Future space transportation system programs must utilize cost reduction tools and techniques in order to become viable entities in the prevailing political and economic environments. Expert system and knowledge based technology can provide this opportunity for significant cost savings. Current active programs may achieve some limited cost benefits via piecemeal applications to identifiable worthwhile targets. But, the real value of the technology lies in the inclusion of its principles in the initial requirements definition phase for the target program and application of these principles throughout the program life cycle. Therefore, it is clear that accommodation of this kind of usage which encompasses the application of technology using sound engineering principles requires the development of tools to accommodate implementation. This means that expert system life cycle standards similar to MIL-STD 2167 are required, various expert system architectures must be developed, e.g., distributed and hybrid distributed systems, large and complex expert systems must easily integrate and interface with procedural language systems such as Ada, and tools that automate the process of knowledge base rule generation from domain experts must be developed to simplify the knowledge acquisition process. Development of these tools and capabilities is realizable within the capabilities of existing technologies. In the current environment of intensive development effort in pursuit of these tools and capabilities, it is reasonable to assume expert system technology will be in a condition suitable to support development of the next generation of space transportation system elements

ICE System: Interruptible control expert system

The Interruptible Control Expert (ICE) System is based on an architecture designed to provide a strong foundation for real-time production rule expert systems. Three principles are adopted to guide the development of ICE. A practical delivery platform must be provided, no specialized hardware can be used to solve deficiencies in the software design. Knowledge of the environment and the rule-base is exploited to improve the performance of a delivered system. The third principle of ICE is to respond to the most critical event, at the expense of the more trivial tasks. Minimal time is spent on classifying the potential importance of environmental events with the majority of the time used for finding the responses. A feature of the system, derived from all three principles, is the lack of working memory. By using a priori information, a fixed amount of memory can be specified for the hardware platform. The absence of working memory removes the dangers of garbage collection during the continuous operation of the controller

DESIGNING OBJECT-ORIENTED REPRESENTATIONS FOR REASONING FROM FIRST-PRINCIPLES

Modeling expert knowledge using "situation-action" rules is not always feasible in knowledge intensive domains involving volatile knowledge (e.g., trading). The explosive search space involved in such domains and its dynamic nature make it extremely difficult to setup a rule base and keep it accurate. An alternative approach suggests that in some domains many of the rules expert use can be derived by reasoning from "first-principles". That approach entails modeling experts' deep knowledge, and emulating reasoning processes with deep knowledge that allow experts to derive many of the rules they use and justify them. This paper discusses the design and implementation of an object-oriented representation for the deep knowledge traders utilize in a business domain called hedging, which is knowledge intensive and involves volatile knowledge. It illustrates how deep knowledge modeled using that representation is used to support reasoning from first-principles. The paper also analyzes features of that representation that we have found to be extremely beneficial in the development of a knowledge-based system called INTELLIGENT-HEDGER. Based on our experience we feel that, with minor modifications, this representation can be used in other managerial domains involving financial reasoning.Information Systems Working Papers Serie

BoilerModel: a qualitative model-based reasoning system implemented in Ada

Effective, inexpensive, and realistic on-going training is required to keep all Naval personnel proficient in their field. Nowhere is this more true than in steam propulsion engineering plants. The complex systems of valves, piping, and components require continuous refresher for watchstanders to perform their jobs safely. BoilerModel is a qualitative expert system designed using model-based reasoning principles and implemented in Ada. It accurately models a 1200 psi D-type boiler and its associated peripherals. The use of fundamental intra-component relationship ("first principles") and constraint propagation result in compact mode because there is no need for the extensive rule base found in conventional expert systems. Implementation in Ada permits the use of concurrent tasking to simulate simultaneous valve propagation found in real-world boiler systems. Additionally, Ada's portability allows BoilerModel to be compiled and run on virtually any machine, thereby making it an affordable and attractive complement to shipboard engineering training.http://archive.org/details/boilermodelquali00stasLieutenant, United States NavyApproved for public release; distribution is unlimited

Fiduciary Law in Financial Regulation

This chapter explores the application of fiduciary duties to regulated financial firms and financial services. At first blush, the need for such a chapter might strike some as surprising in that fiduciary duties and systems of financial regulation can be conceptualized as governing distinctive and nonoverlapping spheres: fiduciary duties police private activity through open-ended, judicially defined standards imposed on an ex post basis, whereas financial regulations set largely mandatory, ex ante obligations for regulated entities under supervisory systems established in legislation and implemented through expert administrative agencies. Yet, as the chapter documents, fiduciary duties often do overlap with systems of financial regulation. In many regulatory contexts, fiduciary duties arise as a complement to, or sometimes substitute for, other mechanisms of financial regulation. Moreover, the interactions between fiduciary duties and systems of financial regulation generate a host of recurring and challenging interpretative issues. The chapter explores the reasons fiduciary duties arise so frequently in the field of financial regulation and provides a structured account of how the principles of fiduciary duties interact with the more rule-based legal requirements that characterize financial regulation. As grist for this undertaking the chapter focuses on a set of roughly two dozen judicial decisions and administrative rulings to illustrate its claims

A machine learning approach to automated construction of knowledge bases for expert systems for remote sensing image analysis with GIS data

Knowledge-based remote sensing image analysis with GIS data is acknowledged as a promising technique. However, the difficulty in knowledge acquisition, a well-known bottleneck in building knowledge-based systems, impedes the adoption of this technique. Automating knowledge acquisition is therefore in demand. This paper presents a machine learning approach to automated construction of knowledge bases for image analysis expert systems integrating remotely sensed and GIS data. The methodology applied in the study is based on inductive learning techniques in machine learning, a subarea of artificial intelligence. It involves training with examples from remote sensing and GIS data, learning using the inductive principles, decision tree generating, rule generating from the decision tree, and knowledge base building for an image analysis expert system. This method was used to construct a knowledge base for wetland classification of Par Pond on the Savannah River Site, SC, using SPOT image data and GIS data. The preliminary results show that this method can provide an effective approach to integration of remotely sensed and GIS data in geographic information processing

The place of expert systems in a typology of information systems

This article considers definitions and claims of Expert Systems ( ES) and analyzes them in view of traditional Information systems (IS). It is argued that the valid specifications for ES do not differ fran those for IS. Consequently the theoretical study and the practical development of ES should not be a monodiscipline. Integration of ES development in classical mathematics and computer science opens the door to existing knowledge and experience. Aspects of existing ES are reviewed from this interdisciplinary point of view

Standardising through concepts: scientific experts and the international development of the HACCP Food Safety Standard

This paper deals with international standard-setting. Using the HACCP food safety standard as the basis of discussion, this paper considers the influence of scientific experts on the regulatory process. What is usually referred to as the diffusion or dissemination of soft or voluntary standards is here explained in terms of transferability of a regulatory concept. It is the ability of scientific experts to transform practices into a universal concept and, conversely, to develop technologies for users which translate the concept into practice, that explains why this reference has travelled so well across countries, industry sectors and historical periods. Scientific experts played a translating role between standard-setters and groups of practical users. This highlights the counter-intuitive distribution of power in standard-setting: while experts dominate the development of generic rules, official rule-makers (such as governments) assert their authority by developing alternative technologies for the appropriation of the standard by users and, sometimes, allow the latter to deviate from experts' universal concepts where these are shown to be problematic

The Evolution of OSI Network Management by Integrated the Expert Knowledge

The management of modern telecommunications networks must satisfy ever-increasing operational demands. Operation and quality service requirements imposed by the users are also an important aspect to consider. In this paper we have carried out a study for the improvement of intelligent administration techniques in telecommunications networks. This task is achieved by integrating knowledge base of expert system within the management information used to manage a network. For this purpose, an extension of OSI management framework specifications language has been added and investigated in this study. A new property named RULE has also been added, which gathers important aspects of the facts and the knowledge base of the embedded expert system. Networks can be managed easily by using this proposed integration