This chapter proposes the fundaments of artificial intelligence (AI) and is the basics of the author's framework that is specialized in transformation initiatives. The proposed natural language programming (NLP) concept is supported by the author's applied holistic mathematical model (AHMM) for AI (AHMM4AI) that is the result of research on AI, business, financial, and organizational transformations using applied mathematical models. This research is based on years of cross-functional research initiatives and on an authentic and proprietary mixed research method that is supported by an authentical version of an AI search tree, which is combined with an internal heuristics motor, which is applied to requirements NLP strategy. The proposed AHMM4AI-based NLP fundamentally functions like the human empiric decision-making process that can be compared to the behaviour-driven development methods, which are optimal for complex software engineering.
TopBackground
This chapter’s background combines NLP, development strategy, Knowledge Management System for AI (KMS4AI), standard DevOps, enterprise architecture, heuristics/mathematical models, technology management, business transformation and business engineering fields; using mapping mechanisms (Ebert, Gallardo, Hernantes, & Serrano, 2016). Building an NLP structure needed for the implementation of strategic Decision Making System for AI (DMS4AI) that is today the major strategic goals for the transformed Entity (Petrock, 2020; Cearley, Walker, & Burke, 2016; Thomas, 2015), as shown in Figure 1. The proposed NLP is a generic and cross-business NLP concept that interacts with a reasoning methods which manage sets of Critical Success Factors (CSF) that can be used by a business transformation or enterprise architectures projects (or simply the Project) in domains related to development AI solutions (Uhl, & Gollenia, 2012); where in this chapter is supported by an adapted insurance case (Jonkers, Band & Quartel, 2012a). The author based his research method on intelligent neural networks and behaviour-driven development, where both methods resemble to the human brain (empirical) processing. This chapter on decision making is a continuation of many years of Research and Development Project for AI (RDP4AI) on various Project processes using decision systems and requirement management systems (Trad & Kalpić, 2019c, 2019d). The NLP concept is business driven and is agnostic to a specific environment, as shown in Figure 1. It is founded on a genuine research framework that in turn is based on many existing industry standards, like the Architecture Development Method for AI (ADM4AI) (The Open Group, 2011a, 2011b).
Figure 1. Technology trends (Petrock, 2020)