Exploring how cognitive interactions between humans and artificial beings can be achieved

Autonomous systems are embodied as smart electronic and software devices. They are capable of operating on their own in familiar and unfamiliar environments. This requires them to:

  • sense all the objects within their surroundings
  • detect motion
  • process the acquired information
  • predict likely changes
  • decide on the best course of action
  • execute their decision
  • observe the environment to learn what else would be required operate with superior performance.

The fulfilment of the assigned mission objectives is the driving force behind a successful operation of autonomous systems.

The core of Intelligent Systems is the ability to represent and reason with knowledge about the real world. This program investigates a range of areas including smart personal assistants, learning algorithms, constraint satisfaction problems, commonsense reasoning, spatio-temporal reasoning, multi-agent systems, and cognitive robotics. It also aims to provide simple, powerful, logically-based systems that allow web documents consisting of data, metadata, ontologies and rules to be represented and processed intelligently by software applications.

Research challenges

Intelligent autonomous systems, also known as artificial beings, will become partners in the workplace and home, able to respond to requests and, not just recognise routines, but attune themselves to specific needs. Therefore, technologies must focus on artificial beings and their collaborative relationships with humans.

Voice, gestures, verbal and facial expressions are used by humans to convey their opinions, intentions and emotions, and autonomous systems need to be able to recognise and these human characteristics, adapt themselves to the ever-changing needs of humans, and potentially express themselves too. Our research explores how cognitive interactions between human and artificial beings may work and be achieved within a particular living environment.


Cooperative systems consist of multiple actors, working together towards accomplishing a mutually agreed objective.

Examples of cooperative systems are numerous. They can be students and teachers in the classroom, employees at their workplace, drivers and pedestrian on the roads, robots in a factory, people at a party, aircrafts in the sky, robots in search-and-rescue operations. However, they can also be unmanned aircrafts in military surveillance and attack missions, or robots on the battlefield. Therefore, cooperative systems attract are of interest not just to engineers and scientists but also to biologists, economists, applied mathematicians, computer scientists and social and political scientists.

Intelligent Control Systems Laboratory

  • Design and development of cooperative driverless vehicles and their embodiment towards a new generation of city transport systems—cybernetic transport systems
  • Collaborative computer games


  • Robocup
  • Non-monotonic reasoning for managing consistency in localisation of mobile robots
  • Robots for people who are blind
  • Face recognition
  • Robot-human interaction in strategy games
  • Teaching robots—soccer teaches social skills to robots

Robotics and Gaming

  • Simulated robot soccer games
  • Intelligent game characters
  • Multiplayer computer games
  • Biped robots
  • Ubiquitous technology in education

Semantic web

  • Nonmonotonic logic programming and its applications in the semantic web (including answer set programming)
  • Reasoning systems for web ontologies (including distributed reasoning systems, modular ontologies, and description logics)

Knowledge, representation and reasoning

  • Modelling and optimising problems involving constraints.
  • Design and developments of theories, architectures, languages, implementations and applications of rational agents.

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