The next phase of computing involves sophisticated, complex systems that perform human like tasks. Our belief is that the management of such complexity will be impossible in the future without self-learning autonomous systems. Therefore, the next challenge is not only understanding “Big Data” but devising complex systems incorporating more and more sophisticated machine learning techniques. Presently, however, software systems that incorporate machine learning are hard to build, deploy, and maintain.
They require a large and highly skilled workforce. Unlike traditional enterprise systems, once built, they often require thousands of hours of on-going, sometimes daily, maintenance to ensure that their predictions and behaviour continue to be accurate and useful. Integrating machine learning systems into traditional enterprise architecture, testing and deployment processes are likewise too complex, partly due to organizational silos that exist between systems engineers and data scientists.
This talk will present a novel business autonomic framework covering topics that deal with the design, implementation, deployment and lifecycle management of such closed loop self-learning autonomic systems. A real example will also be presented together with an abstraction of the main principles extracted from the framework. Also, software engineering techniques that ensure correctness autonomic systems decisions will be presented and analysed. Simulation and testing as current industrial practices will be discussed and the gaps towards assurance and formal verification of autonomic properties that will presented.
Speakers: Dr Botond Virginas from British Telecom & Dr Sofia Meacham from Bournemouth University.
Refreshments will be available from 5.15pm.
For overseas delegates who wish to attend the event please note that BCS does not issue invitation letters.
Bookings for this event will close Saturday 19 May @ 10pm.
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