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The building industry, through its structure and its mandate, faces endemic information problems; expert systems are expected to impact positively. Expert systems are suited to situations of uncertainty; knowledge and reasoning are separated, allowing easier updating. Knowledge acquisition from human experts is difficult and problems of information reliability arise, suggesting the scope for cooperation between knowledge engineers and documentalists familiar with the domain. In building, prevailing conditions seem to indicate the appropriateness of expert systems, particularly during the design phase; however, written documentation and general research results are rarely consulted. This highlights the need for an information ‘refining’ stage between production and use. It is easier to set up expert systems for specialised sub‐domains; however, on‐going research is attempting to develop a comprehensive approach to project‐specific information that would be operational from initial design through to completed construction. Criteria for a comprehensive design information system can be listed.

Existing regulatory frameworks for identifying and treating historic buildings and places reflect deference to expert rule, which privileges the values of a small number of heritage experts over the values of the majority of people who visit, work, and reside in historic environments. The purpose of this paper is to explore a fundamental shift in how US federal and local preservation laws address built heritage by suggesting a dynamic, adaptive regulatory framework that incorporates heterodox approaches to heritage and therefore is capable of accommodating contemporary sociocultural values.

The overall approach used is a comparative literature review from the fields of heterodox/orthodox heritage, heterodox/orthodox law, adaptive management, and participatory methods to inform the creation of a dynamic, adaptive regulatory framework.

Tools such as dialogical democracy and participatory action research are sufficiently pragmatic in implementation to envision how an adaptive regulatory framework could be implemented. This new framework would likely require heterodox definitions of law that move beyond justice as a primary purpose and broaden the nature of legal goods that can be protected while addressing discourses of power to benefit a larger group of stakeholders.

The authors suggest that an adaptive regulatory framework would be particularly beneficial for architectural and urban conservation planning, as it foregrounds considerations other than property rights in decision-making processes. While such a goal appears to be theoretically possible, the challenge will be to translate the theory of an adaptive regulatory framework into practice as there does not appear to be any precedent for its implementation. There will be issues with the need for increased resources to implement this framework.

To date, there have been few, if any, attempts to address critical heritage studies theory in the context of the regulatory environment. This paper appears to be the first such investigation in the literature.

Existing regulatory frameworks for identifying and treating historic buildings and places reflect deference to expert rule, which privilege the values of a small number of heritage experts over the values of the majority of people who visit, work, and reside in historic environments. To address this problem, the purpose of this paper is to explore a fundamental shift in how US federal and local preservation laws address built heritage by suggesting a dynamic, adaptive regulatory framework that incorporates heterodox approaches to heritage and therefore is capable of accommodating contemporary sociocultural values.

The overall approach the authors use is a comparative literature review from the fields of heterodox/orthodox heritage, heterodox/orthodox law, adaptive management, and participatory methods to inform the creation of a dynamic, adaptive regulatory framework.

Heterodox heritage emphasizes the need for a bottom-up, stakeholder-driven process, where everyday people’s values have the opportunity to be considered as being as valid as those of conventional experts. Orthodox law cannot accommodate this pluralistic approach, so heterodox law is required because, like heterodox heritage, it deconstructs power, values participation, and community involvement.

Orthodox heritage conservation practice disempowers most stakeholders and empowers conventional experts; this power differential is maintained by orthodox law.

To date, there have been few, if any, attempts to address critical heritage studies theory in the context of the regulatory environment. This paper appears to be the first such investigation in the literature.

Existing supply chain (SC) performance models are not able to cope with the potential of intensive SC digitalisation and establish a relationship between decisions and decision criteria. The purpose of this paper is to develop an integrated knowledge-based system (KBS) that creates a link between decisions and decision criteria (attributes) and evaluates the overall SC performance.

The proposed KBS is grounded on the fuzzy analytic hierarchy process (fuzzy AHP), which establishes a relationship between short-term and long-term decisions and SC performance criteria (short-term and long-term) for accurate and integrated Overall SC performance evaluation.

The proposed KBS evaluates the overall SC performance, establishes a relationship between decisions (long-term and short-term) and decision criteria of SC functions and provides decision makers with a view of the impact of their short-term or long-term decisions on overall SC performance. The proposed system was implemented in a case company where the authors were able to develop a SC performance monitoring dashboard for the company’s top managers and operational managers.

The proposed KBS assists organisations and decision makers in evaluating their overall SC performance and helps in identifying underperforming SC functions and their associated criteria. It may also be considered as a tool for benchmarking SC performance against competitors. It can efficiently point to improvement directions and help decision makers improve overall SC performance.

The proposed KBS provides a holistic and integrated approach, establishes a relationship between decisions and decision criteria and evaluates overall SC performance, which is one of the main limitations in existing supply chain performance measurement systems.

When the history of the financial crisis, stock market crash, and ensuing recession of 2007–2009 is written, the appropriate focus would be on the role that “expertise” played in almost every chapter of the story. From the expertise of the mathematicians who guided the models used by financial institutions, to the expertise of those who developed new kinds of mortgage instruments that required very low down payments, to the expertise of US policymakers who told us that new regulations to encourage more widespread homeownership would be an engine of economic growth and prosperity, the actions of those who knew better eventually littered the financial landscape with their errors. In addition to the prior list, which is hardly exhaustive, perhaps the most central set of experts in the story were those associated with the Federal Reserve System, the US central bank. The Fed rarely shies away from using its expertise to cloak its choices in a cloud of jargon and technicalities, even as its every move has significant effects across the US economy and the whole globe. The Fed's decisions to keep interest rates so low after 9/11 and to seize unprecedented powers in the wake of the recession that inevitably followed that earlier policy were both the latest examples of the history of the Fed's ever-increasing claims to expertise that have led to expanding powers and new and more damaging mistakes.

Applies a parallel backward‐chaining technique to a rule‐based expert system on a shared‐memory multiprocessor system. The condition for a processor to split up its search tree (task‐node) and generate new OR nodes is based on the level in the goal tree at which the task‐node is found. The results indicate satisfactory speed‐up performance for a small number of processors (< 10) and a reasonably large number of rules.

Automating the construction of machine‐interpretable knowledge‐bases is one of the immediate next moves in the emerging technology of information. Feasibility of computer induction of new knowledge from examples has been shown in more than one laboratory. Means are described for generating knowledge‐based programs that are automatically guaranteed analysable and executable by machine and human brain alike.

Recent seminars in Munich, London and Rome, which were sponsored by the International Defense Electronics Association (IDEA), comprehensively cover the state of the art in Expert Systems and gave the cybernetician in particular, an insight into this fascinating area.

The purpose of this paper is to discuss the case-based reasoning (CBR) approach to improve microcredit initiatives by means of providing a borrower risk rating system.

The CBR approach has been used to consider the Kiva microcredit system, which provides a characterization (rating) of the risk associated with the field partner supporting the loan, but not of the specific borrower which would benefit from it. The authors discuss how the combination of available historical data on loans and their outcomes (structured as a case base) and available knowledge on how to evaluate the risk associated with a loan request can be used to provide the end users with an indication of the risk rating associated with a loan request based on similar past situations.

The adopted approach is applied and evaluated employing a selection of cases from individual loans. From this perspective, the case base and the codified knowledge about how to evaluate risks associated with a loan represent two examples of knowledge IT artifacts.

The originality of the work lies in borrower risk rating in online indirect peer-to-peer microcredit lending platforms. The case base and the codified knowledge are the two contributions in knowledge IT artifacts.