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Powering innovation in artificial intelligence with Open Access research...

Artificial intelligence (AI) and machine learning (ML) together represent a research frontier with a wide variety of discipline specific applications. At Strathclyde researchers in Computer & Information Sciences are exploring improved AI planning models to enable improved decision making by automous agents. Meanwhile, research conducted by the Aerospace Centre of Excellence is using AI and computational techniques to optimize the efficacy of certain astronautic applications. This includes 'global trajectory optimization' to aircraft and spacecraft design, from the planning and scheduling for autonomous vehicles to the synthesis of robust controllers for airplanes or satellites.

AI is also transforming the research agenda within Finance, where researchers are exploring the potential of AI and machine learning in evaluating banking risks and in new, emerging aspects of FinTech.

Explore some of this Open Access research from Computer & Information Sciences, Aerospace Centre of Excellence and Finance. Or explore all of Strathclyde's Open Access research...

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Group by: Publication Date | Item type | No Grouping
Jump to: 2010 | 2008 | 2007 | 2006 | 2005
Number of items: 7.

2010

Newton, M. A. H. and Levine, J.; (2010) Implicit Learning of Macro-Actions for Planning. In: Proceedings of the 2010 conference on ECAI 2010. ACM, New York, pp. 323-328. ISBN 978-1-60750-605-8

2008

Murray, R. and Newton, M. (2008) Facilitating writing for publication. Physiotherapy, 94 (1). pp. 29-34. ISSN 0031-9406

Shahriar, A.Z.M. and Akbar, M.M. and Rahman, M.S. and Newton, M.A.H. (2008) A multiprocessor based heuristic for multi-dimensional multiple-choice knapsack problem. Journal of Supercomputing, 43 (3). pp. 257-280. ISSN 0920-8542

2007

Newton, M. A. H. and Levine, J.; (2007) Evolving macro-actions for planning. In: Proceedings of the Workshop on AI Planning and Learning held at ICAPS 07. UNSPECIFIED.

Newton, M.A. Hakim and Levine, John and Fox, Maria and Long, Derek; Boddy, Mark and Fox, Maria and Thiebaux, Sylvie, eds. (2007) Learning macro-actions for arbitrary planners and domains. In: Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling (ICAPS 2007). AAAI Press, California, USA, pp. 256-263. ISBN 1577353447

2006

Newton, M. A. H. and Levine, J. and Fox, M. and Long, D.; (2006) Learning macro-actions genetically from plans. In: Proceedings of the 25th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG 2006). UNSPECIFIED.

2005

Newton, M. A. H. and Levine, J. and Fox, M.; (2005) Genetically evolved macro-actions in AI planning problems. In: Proceedings of the 24th Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG 2005). UNSPECIFIED, pp. 163-172.

This list was generated on Mon Aug 10 09:29:50 2020 BST.