Self-funded PhD opportunities

Modelling Strategic Management with Multiple Intelligent Agents

  • Application end date: 15th June, 2018
  • Funding Availability: Self-funded PhD students only
  • Department: School of Computing
  • PhD Supervisor: Professor Adrian Hopgood, Dr Jana Ries, Dr Alan Tait

Project code: CCTS4290618

Project in detail

This project concerns the development of artificial intelligence (AI) for high-level strategic management. Typical AI projects to date have been narrowly constrained and highly operational, so the project will require a technological and intellectual step forward.

As strategic management requires a broad range of perspectives, with balanced oversight, it is ideally suited to modelling with a multiagent approach using the blackboard framework. The different aspects of strategic management can be modelled by independent specialised software agents that inform the overall judgements. The established academic models typically include stages such as analysis, strategy formulation, goal setting, structure, and control/feedback.

The use of the balanced scorecard is proposed as a complementary strategic planning and management decision-making tool. Individual optimizations may use genetic algorithms with a performance function derived from the balanced scorecard, while the multi-agent framework will draw together the multiple strategic perspectives.

Prof Hopgood has led the design and implementation of a software framework that would be suited to this challenge, subject to further development within the scope of the project. Known as DARBS (Distributed Algorithmic and Rule-based Blackboard System), it allows a variety of different software tools to work collaboratively as independent intelligent agents.

You may also wish to consider the linked project, "The Next Generation Strategist: exploring the competences required for engaging in strategy".

You may also wish to consider the linked project, "The Next Generation Strategist: exploring the competences required for engaging in strategy".

Indicative References

  • Levine, S.S., Bernard, M., & Nagel, R. (2017). Strategic Intelligence: The Cognitive Capability to Appreciate Competitor Behavior. Strategic Management Journal, 38 (12): 2390-2423.

  • Hopgood, A.A. (2012). Intelligent Systems for Engineers and Scientists, 3rd edition, CRC Press.

  • Khmeleva, E., Hopgood, A.A., Tipi, L. and Shahidan, M. (2017). "Fuzzy-Logic Controlled Genetic Algorithm for the Rail-Freight Crew-Scheduling Problem", KI - Künstliche Intelligenz.

Supervisor Profiles

Professor Adrian Hopgood

Dr Jana Ries

Dr Alan Tait

Entry requirements

You’ll need a good first degree from an internationally recognised university (depending upon chosen course, minimum second class or equivalent) or a Master’s degree in an appropriate subject. Exceptionally, equivalent professional experience and/or qualifications will be considered. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0. 

Specific candidate requirements 

  • Background in computer science, software engineering, information systems, or a related subject. 
  • A keen interest in business and management. 
  • Excellent interpersonal and organisational skills 


Informal enquiries are encouraged and can be made to Professor Adrian Hopgood at (02392 84 2946) or Dr Jana Ries at (02392 844023).

For administrative and admissions enquiries please contact

How to Apply

You can apply online at  You are required to create an account which gives you the flexibility to save the form, log out and return to it at any time convenient to you. A link to the online application form and comprehensive guidance notes can be found at

Start date: 1st October 2018

Application deadline:  15th June 2018

Interview date: week commencing 25th June 2018

When applying please note the project code – CCTS4290618

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