Towards intelligence engineering in agent-based systems

Abstract EN

In this paper, we consider intelligence as an explicit requirement in modern information systems and introduce intelligence engineering as the application of a systematic and disciplined approach to the development, operation, and maintenance the intelligence.

After categorizing intelligence sub-characteristics based on an extensive quantitative analysis, we choose learning as the most frequent sub-characteristic of intelligence and present a process for specifying learning in intelligent systems.

This process is based on Organizational Multiagent System Engineering (O-MaSE) process framework and extends this framework to cover learning analysis concepts.

More precisely, by using O-MaSE meta-model and learning analysis meta-models, alongside applying the process for development a system, we study the potentials of the process framework in specifying learning concepts.

Based on the discovered shortcomings of the process, we propose extensions to enrich the process for specifying learning, namely for Requirements gathering, Goal modeling, Knowledge modeling and Environment specification.

The applicability of the extended O-MaSE is evaluated by applying it on a book trading system.

Based on this systematic process, software development benefits from the more specific assumptions on capabilities expected for learning, and it moves towards more sophisticated engineering practices which prevents implicit or ad-hoc activities for.