MSc in Intelligent Autonomous Systems

Master

In Aberystwyth

Price on request

Description

  • Type

    Master

  • Location

    Aberystwyth (Wales)

  • Duration

    Flexible

This Master gives students broad experience of Artificial Intelligence of Autonomous Systems, and good training for further research. This knowledge is then applied in the field of intelligent autonomous systems, where applications range from controlling mobile robots, to diagnosing problems on spacecraft, to intelligent, information-gathering web-bots. This degree is industrially relevant, but also provides excellent research preparation for students wishing to carry out research towards a PhD in any area of Intelligent Systems.

Important information

Documents

  • MSc-IAS 2009 Brochure

Facilities

Location

Start date

Aberystwyth (Ceredigion)
See map
Aberystwyth University, Llandinam Building, SY23 3DB

Start date

On request

Questions & Answers

Add your question

Our advisors and other users will be able to reply to you

Who would you like to address this question to?

Fill in your details to get a reply

We will only publish your name and question

Reviews

Course programme

This degree links to the research of three of our research groups:

  • Advanced Reasoning

The Advanced Reasoning Group (ARG) aims to conduct innovative research in qualitative and approximative reasoning, including methods of knowledge representation, model generation and refinement, and model-based problem solving.

The ARG has an excellent track record of developing the scientific foundations necessary for building intelligent decision support systems, especially in crime detection and prevention, engineering design analysis, and computer-based diagnosis. In particular, the group is well known for its ground-breaking work on automated diagnostic and failure analysis for circuit design in the automotive industry, and its invention of fuzzy-rough semantics-preserving techniques for explicit knowledge model formulation and simplification. The group's research also includes other advanced computational intelligent techniques, e.g. evolutionary algorithms and meta-heuristics.

Research Topics

  • Multiple failure FMEA and sneak circuit analysis
  • Mode-based whole lifecycle automated system analysis
  • Qualitative model-based learning
  • Knowledge extraction over high dimensional data sets
  • Compositional modeling and preference handling.

Applications of the above techniques are wide-reaching, ranging from laboratory demonstrations (e.g. Metabolic pathway identification and simulation, and crime scenario construction and investigation) to commercial productions (e.g. automotive and aeronautical fault diagnosis, and consumer sensitive data analysis).

  • Computational Biology

The Computational Biology Group (CBG) conducts research in two closely related research areas: the automation of science and the formalisation of science. Both areas of research are central to the future of computer science and to that of the natural sciences.

The group's work focuses on abstracting from successful examples of scientific practice. To this end the group has become deeply involved in solving important biological problems (in functional genomics, systems biology, metabolomics, etc.) and chemical problems (in drug design, coherent control, etc.).

One of CBG's most important contributions to science has been to originate the concept and develop the first Robot Scientist, a computer system that can automatically: generate hypotheses to explain a scientific problem; form efficient experiments to test these hypotheses; physically execute the experiments using robotics; analyse the results; and repeat the cycle. Robot Scientists have the potential to fundamentally alter the practice of science

  • Intelligent Robotics

The Intelligent Robotics Group (IRG) is one of the largest and best-known robotics groups in the UK, carrying out research that falls under the umbrella of "unconstrained environments", in the context of both software and hardware. Biologically inspired models of control and cognition provide a common theme to much of the group's work. Robot vision systems work has also followed this theme along with more traditional vision techniques. Work in space robotics has been prominent with involvement in Beagle2 and several future Mars missions.

There is a significant computer vision component in the group: feature-based localisation of aerial platforms for planetary exploration; extraction of the 3D structure of complex objects; appearance-based methods to provide mobile robots with various capabilities including topological mapping and pose stabilisation. The vision research has gone beyond a supporting role for robotics, reflected in the Department's recent strategy to further develop the Vision Research Group.

MSc in Intelligent Autonomous Systems

Price on request