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KNOWLEDGE IS POWER An organization’s best experts develop unique capabilities for reasoning about particular subject areas. Applying this knowledge enables them to skillfully use information to make effective decisions. KNOWLEDGE_BASED SYSTEMS Developing software applications that apply expert knowledge to solve various problems within the organization is very challenging. Such systems require explicit representation of expert knowledge. Knowledge Engineers have to be able to handle unstructured information, and unusual situations. Knowledge Engineering Services -- A Core Capability for ASI ASI has almost 20 years of experience building knowledge-based systems. Knowledge Engineering Process At a high level, this is a two step transformation:  | Knowledge Elicitation -- transform raw knowledge into organized knowledge. This is also known as knowledge acquisition. | | | Knowledge Implementation -- transform organized knowledge into operational knowledge. | 
Knowledge Elicitation Knowledge elicitation is the process of capturing knowledge through a series of steps, procedures, subject matter expert interviews and other related activities that provide information that can be used to understand the domain area and its relationships to the overall project goal. | | Natural Knowledge - Knowledge in its raw form, such as an expert’s accumulated experience and ability to apply it when reasoning about a domain (whether consciously or unconsciously). | | | Organized Knowledge - Knowledge organized so that it can be easily understood by humans. | Knowledge Elicitation Activities include: | | The knowledge engineer works closely with the domain expert to capture the expert's knowledge in a knowledge base. | | | Iterative, collaborative process | | | Identify goals and scope | | | Capture and organize knowledge from interviews, research | | | Identify data sources & analysis algorithms | | | Define system actions & user interaction | | | Access to subject matter experts is critical. | | | Access to experts is required throughout the knowledge engineering lifecycle. | | | Our knowledge engineers work very closely with your subject matter experts to elicit and capture organized knowledge. | Knowledge Implementation | | How do I know it will work? How will you test the system?
The Pre-Act® plan-goal graph, concept graph, and situated script representations are all designed to capture the assessment, planning, and execution processes that a human carries out; in fact, part of their purpose is to allow a human to understand the system’s behaviors. These graph structures and their explicit representations of constraints, relationships, and alternatives lend themselves readily to evaluation and verification by domain experts. This evaluation would be followed by a test of the prototype using simulated data, if possible, and field tests of the solution prototype. Even during field testing, the domain experts can continue to monitor the system to understand the reasons for each agent’s actions. | | | Integrated Knowledge Environment (IKE) - Pre-Act® now comes with IKE, our GUI-based Integrated Knowledge Environment, to cut your greatest cost for building intelligent systems: the knowledge engineering. Good tools make knowledge engineering faster and cheaper. ASI focuses on producing highly usable tools for building knowledge bases for Pre-Act,® such as by providing a palette of knowledge constructs for designing domain-specific planning capabilities. | |
