Proposal of an Inference Engine Architecture for Business Rules and Processes

Author(s):  
Grzegorz J. Nalepa ◽  
Krzysztof Kluza ◽  
Krzysztof Kaczor
2018 ◽  
Author(s):  
Biplav Srivastava ◽  
Anton V ◽  
Anton V. Riabov ◽  
Adi Botea

Planning has been used in many industrial applications but they are still few and far between compared to other AI sub-fields like learning, constraints and (business) rules. In this paper, we highlight key considerations important in practice and articulate the issues therein which if addressed, we anticipate, will trigger a new wave of planning-based applications.


2012 ◽  
Author(s):  
Jacopo Urbani ◽  
Spyros Kotoulas ◽  
Jason Massen ◽  
Frank van Harmelen ◽  
Henri Bal

Author(s):  
Matteo Gargantini ◽  
Carmine Di Noia ◽  
Georgios Dimitropoulos

This chapter analyzes the current regulatory framework for cross-border distribution of investment funds and submits some proposals to improve it. The chapter is organized as follows. Section 2 provides a schematic description of the legal taxonomy for collective investment schemes. Section 3 addresses the EU disclosure regimes that apply to the distribution of various types of investment funds. Sections 4 and 5 consider conduct-of-business rules and, respectively, the legal framework for the allocation of supervisory powers on product regulation when fund units are distributed in more than one country. Section 6 provides some data that help assess the performance of the current framework for cross-border distribution. It then analyzes some of the residual legal rules and supervisory practices that still make cross-border distributions of funds more burdensome than purely national distributions, whether these restrictions are set forth in the country where investors are domiciled (Section 7) or in the fund's home country (Section 8).


Author(s):  
Robert L. Grant ◽  
Bob Carpenter ◽  
Daniel C. Furr ◽  
Andrew Gelman

In this article, we present StataStan, an interface that allows simulation-based Bayesian inference in Stata via calls to Stan, the flexible, open-source Bayesian inference engine. Stan is written in C++, and Stata users can use the commands stan and windowsmonitor to run Stan programs from within Stata. We provide a brief overview of Bayesian algorithms, details of the commands available from Statistical Software Components, considerations for users who are new to Stan, and a simple example. Stan uses a different algorithm than bayesmh, BUGS, JAGS, SAS, and MLwiN. This algorithm provides considerable improvements in efficiency and speed. In a companion article, we give an extended comparison of StataStan and bayesmh in the context of item response theory models.


2010 ◽  
Vol 50 (1) ◽  
pp. 665
Author(s):  
Ally Oliver

A permit to work (PTW) system is a formal system used to control certain types of work that are identified as potentially hazardous. It is also a means of communication between facility management, plant supervisors and operators, and those who carry out the hazardous work. The essential features of a PTW system are: • Clear identification for who may authorise particular jobs, and who is responsible for specifying the necessary precautions; • Training and instruction in the issue and use of permits; and, • Monitoring and auditing to ensure that the system works as intended. PTW systems are the key to ensuring safe execution of activities at site, yet there are many approaches to how permit systems can, and should, work. Each approach has its own merits and weaknesses. Woodside recognised that, as part of its ongoing program to improve the safety of its workers, there existed significant scope for a new and better work management system. After many years of incremental evolution of the PTW and the fragmentation of the parent system as each facility developed its own variation, it was evident that a completely new system embracing modern technology would provide the best result, while simultaneously standardising Woodside with one common and centralised system. The divergence of the systems over time caused increasing difficulty in managing changes to the PTW system across all sites and in benchmarking to determine best practice. A centralised system would remove accountability from facilities for the development of the business rules, and instead ensure they focussed on compliance with the rules. The new system would adopt key learnings from the industry’s history and address root causes of past incidents. It would also enable the ability to adopt future learnings and become a conduit for rapid integration into the working practices on all sites. The Integrated Safe System of Work (iSSoW) developed by Woodside adopts best practices from permit systems worldwide and combines them with new innovative management features. The system is administered through a simple-to-use computer interface, with incorporation of many of the business rules into the software package. The iSSoW is now in place on all Woodside facilities (platforms, not-normally manned installations, FPSO’s and onshore plants). With nearly 4,000 users, the implementation has required careful coordination, and been supported by a comprehensive training programme. The system has been demonstrated to be both effective and efficient. Effectiveness—the improvement of safety performance—was the primary objective. The system has raised work party hazards awareness, and has resulted in significant improvements in working practices company-wide. Efficiency was a secondary goal, and is made possible through streamlining in the user-interface. The introduction of the new system complements Woodside’s work to develop an improved safety culture, and brings consistency across all sites and all shifts—essential features as our industry struggles to deal with the growing scarcity of skills and experience. The system is now being reviewed by organisations across many industry and service sectors in Australia, and has been implemented in the power industry. This paper discusses the attributes of the system, the many challenges associated with development and large-scale implementation of such a core system, and the additional opportunities the system presents. Using a case study of implementation of iSSoW onto the Woodside operational facilities, it highlights the critical success factors of introducing iSSoW on a company-wide basis.


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