MIS41070 Smart Systems

Academic Year 2018/2019

Smart systems are systems which are adaptive, automated, robust, resilient, efficient. Often they are distributed/decentralised for robustness (no single point of failure), which requires a new way of designing them. Often they are required to be capable of managing their own complexity. They may take inspiration from the natural world, in which extraordinary outcomes (e.g. adaption of organisms to their environment) are achieved despite no central plan or goal. Often they exhibit some aspects of “intelligence”, though this is a contested term. Increasingly, smart business systems are dealing with the outside world directly through (for example) image recognition, rather than being limited with “closed” access to internal databases.

Topics:
● The automation of business
● Examples of complex/adaptive system
● Heuristics, metaheuristics, self-adaptive methods & natural computing
● Artificial intelligence

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Curricular information is subject to change

What will I learn?

Learning Outcomes:

On completion of the module students should be able to:
● Describe the history of automation, with understanding of common motives and technological enablers
● Distinguish between centralised and decentralised systems and discuss the pros and cons of each
● Describe and execute modern heuristic search and modelling methods from natural computing
● Describe some of the implications of artificial intelligence and smart systems for automation, employment, costs, and society.