Interoperability and the Need for Intelligent Software: A Historical Perspective

With the objective of defining the interoperability theme of this year’s conference it is the purpose of this paper1 to trace the evolution of intelligent software from data-centric applications that essentially encapsulate their data environment to ontology-based applications with automated reasoning capabilities. The author draws a distinction between human intelligence and component capabilities within a more general definition of intelligence; - a kind of intelligence that can be embedded in computer software. The primary vehicle in the quest for intelligent software has been the gradual recognition of the central role played by data and information, rather than the logic and functionality of the application. The three milestones in this evolution have been: the separation of data management from the internal domain of the application; the development of standard data exchange protocols such as XML that allow machine interpretable structure and meaning to be added to data exchange packages; and, the ability to build information models that are rich in relationships and are thereby capable of supporting the automated reasoning capabilities of software agents. The author suggests that the vision of a Semantic Web environment in which ontology-based Web services with intelligent capabilities are able to discover each other and individually or in self-configured groups perform useful tasks, is not only feasible but imminently realizable. The capabilities of an experimental proof-of-concept system featuring semantic Web services that was demonstrated during the 2002 meeting of this annual conference series is described in summary form

Information-Centric Decision-Support Systems: A Blueprint for \u3cem\u3e‘Interoperability’\u3c/em\u3e

For the past 20 years the US military services have suffered under the limitations of stove-piped computer software applications that function as discrete entities within a fragmented data-processing environment. Lack of interoperability has been identified by numerous think tanks, advisory boards, and studies, as the primary information systems problem (e.g., Army Science Board 2000, Air Force SAB 2000 Command and Control Study, and NSB Network-Centric Naval Forces 2000). Yet, despite this level of attention, all attempts to achieve interoperability within the current data-centric information systems environment have proven to be expensive, unreliable, and generally unsuccessful

Reverse-Engineering the brain: The parts are as complex as the whole.

The purpose of this paper is to review the current state of neuroscience research with a focus on what has been achieved to date in unraveling the mysteries of brain operations, major research initiatives, fundamental challenges, and potentially realizable objectives. General research approaches aimed at constructing a wiring diagram of the brain (i.e., connectome), determining how the brain encodes and computes information, and whole brain simulation attempts are reviewed in terms of strategies employed and difficulties encountered. While promising advances have been made during the past 50 years due to electron microscopy, the development of new experimental methods, and the availability of computer-enabled high throughput imaging systems, brain research is still greatly encumbered by inadequate monitoring and recording capabilities. Four hypotheses relating to comprehension through the assembly of parts, formation of memories, influence of genes, and synapse formation are described as plausible explanations even though they cannot be validated at this time. By assessing the feasibility of overcoming the principal problems that beleaguer brain research in comparison with the potential benefits that can be derived from even partial achievement of the goals the author concludes that the significant investment of government funding is justified

Transition From Data to Information

It is often lamented that we human beings are suffering from an information overload. This is a myth; as shown in Fig.1, there is no information overload. Instead, we are suffering from a data overload. The confusion between data and information is not readily apparent and requires further explanation. Unorganized data are voluminous but of very little value. Over the past 15 years, industry and commerce have made significant efforts to rearrange this unorganized data into purposeful data, utilizing various kinds of database management systems. However, even in this organized form, we are still dealing with data and not information

The Five Tribes of Machine-Learning: A Brief Overview

This paper reviews recent advances in automated computer-based learning capabilities. It briefly describes and examines the strengths and weaknesses of the five principal algorithmic approaches to machine-learning, namely: connectionism; evolutionism; Bayesianism; analogism; and, symbolism. While each of these approaches can demonstrate some degree of learning, a learning capability that is comparable with human learning is still in its infancy and will likely require the combination of multiple algorithmic approaches. However, the current state reached in machine-learning suggests that Artificial General Intelligence and even Artificial Superintelligence may indeed be eventually feasible

Intuition: Role, Biases, Cognitive Basis, and a Hypothetical Synergistic Explanation of Intuitive Brain Operations

This paper explores the characteristics of the intuitive responses that are generated by our brain continuously in an automatic and effortless manner. However, while intuition is a very powerful mechanism, it is also subject to many biasing influences. The author discusses the role of intuition, examines representative examples of biasing influences, compares cognitive theories of intuition advanced by Simon (2002), Klein (2003 and 1999), and Kahneman (2011), and then advances a hypothetical explanation of the neurological operations underlying intuition based on Hebbian rules (Hebb 1949) of plasticity in combination with synergetic principles

The Meaning of an Information-Centric Computer Environment

It is often lamented that we human beings are suffering from an information overload. This is a myth, as shown in Fig.1 there is no information overload. Instead we are suffering from a data overload. The confusion between data and information is not readily apparent and requires further explanation. Unorganized data are voluminous but of very little value. Over the past 15 years, industry and commerce have made significant efforts to rearrange this unorganized data into purposeful data, utilizing various kinds of database management systems. However, even in this organized form, we are still dealing with data and not information

The Future of Computing: \u3cem\u3eCyberspace\u3c/em\u3e

This paper traces trends in the technological advances of computer and communication systems and examines the promises of the Information Society: global information sharing; and, intelligent decision-support. The technological developments that will lead to the realization of Cyberspace, an information rich environment in which virtual reality capabilities couple directly to the human senses, is explored in terms of five essential components: information processing requirements; communication networks; computing devices (i.e., platforms); hardware and software user-interfaces; and, the meaningful representation of information. Attention is drawn to the critical role played by information representation in a Cyberspace environment. The author argues that the communication infrastructure must become more than a message passing facility. It must have some understanding of the information it is transmitting. If this fundamental requirement is met then Cyberspace will present human society with an unprecedented potential for leveraging the capabilities of the individual members of society for their own benefit and the collective benefit of mankind

The Construction of Two Prototype Multi-Storey Air-Supported Buildings

To treat a multi-storey building as a large, inflatable container forces the architect to consider design and construction criteria foreign to the building industry at large. While satisfactory progress has been made in the development of theoretical solutions for problems dealing with the structural and planning implications of a hyperbaric building environment, the time has come to consider practical issues. This paper discusses the design, construction and operation of two prototype, multi-storey, air-supported buildings. The first building was completed in November, 1972 at the School of Building, University of New South Wales, Australia, and the second building was completed in April, 1973 at the School of Architecture and Environmental Design, California Polytechnic State University, San Luis Obispo, California, United States. In both cases the buildings were treated as student projects and aimed at the development of planning, organizational and constructional skills in the participating undergraduate student

Pneumatic Construction Applied to Multistory Buildings

Extension of the principles of pneumatic construction to include multistory buildings is discussed by Peter R. Smith, Senior Lecturer in Architectural Science at The University of Sydney (Australia) and Jens G. Pohl, Lecturer, School of Architecture and Building, University of New South Wales