ICADS: A cooperative decision making model with CLIPS experts

A cooperative decision making model is described which is comprised of six concurrently executing domain experts coordinated by a blackboard control expert. The focus application field is architectural design, and the domain experts represent consultants in the area of daylighting, noise control, structural support, cost estimating, space planning, and climate responsiveness. Both the domain experts and the blackboard were implemented as production systems, using an enhanced version of the basic CLIPS package. Acting in unison as an Expert Design Advisor, the domain and control experts react to the evolving design solution progressively developed by the user in a 2-D CAD drawing environment. A Geometry Interpreter maps each drawing action taken by the user to real world objects, such as spaces, walls, windows, and doors. These objects, endowed with geometric and nongeometric attributes, are stored as frames in a semantic network. Object descriptions are derived partly from the geometry of the drawing environment and partly from knowledge bases containing prototypical, generalized information about the building type and site conditions under consideration

Is there Progress toward Sustainability?: Despite the inherent human resistance to change.

The theme of this paper is to briefly survey the status of current efforts to maintain our natural environment and then discuss prospects for achieving future sustainability. The author finds that while there has been general recognition of the need for environmental sensitivity and conservation of natural resources, progress toward achieving sustainability goals has been slow. A principal reason for this lack of action is found in the reactive nature of the human species. Situated by biological design in our environment we typically respond to environmental changes only after they have occurred. Accordingly, while a number of revolutionary proposals have been made in recent years that would ensure sustainability almost indefinitely they are unlikely to be implemented proactively. Instead they will be implemented piecemeal by necessity when it is almost too late to avert the near disaster situations that they were intended to prevent from occurring

Challenging Computer Software Frontiers and the Human Resistance to Change

This paper examines the driving and opposing forces that are governing the current paradigm shift from a data-processing information technology environment without software intelligence to an information-centric environment in which data changes are automatically interpreted withinthe context of the application domain. The driving forces are related to the large quantity of dataand the complexity of networked systems that both call for software intelligence. The opposing forces are non-technical and due to the natural human resistance to change. Based on this background the paper describes current information-centric technology, proposes avision of intelligent software system capabilities, and identifies four areas of necessary research.Most urgent among these are the ability to dynamically extend and merge ontologies and semantic search capabilities that can be initiated either by human users or software agents.Longer term research interests that pose a more severe challenge are related to the translation of emerging theoretical hierarchical temporal memory (HTM) concepts into usable software capabilities and the automated interpretation of graphical images such as those recorded bysurveillance video cameras

Beyond Human Intelligence: \u3ci\u3eRedefining Intelligence\u3c/i\u3e

The digital revolution driven by global connectivity, computing as a utility, artificial intelligence, and information sharing on an unprecedented scale is forcing the redefinition of intelligence in a broader context that extends beyond human intelligence. This paper addresses the principal characteristics of biological intelligence, as it exists on planet Earth and the form it may take in an extraterrestrial context. Human intelligence, as the most evolved form of biological intelligence on Earth, is treated as the aggregation of multiple intelligences that cannot be encapsulated in a single metric such as an Intelligence Quotient (IQ). The concept of a postbiological civilization that combines biological intelligence with artificial intelligence is presented as a cultural evolution that is driven by the replacement of the propagation of genes with some alternative replicator. The paper concludes with speculations of the nature of extraterrestrial intelligence that is likely to be much older and far superior to biological intelligence, and may be of a form that is incomparable to human intelligence and therefore unrecognizable by humans

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