Artificial systems that fulfil one or both of the following requirements:

• they can achieve general goals in a largely unsupervised way, and persevere under adverse or uncertain conditions; adapt, within reasonable constraints, to changing service and performance requirements, without the need for external re-programming, re-configuring, or re-adjusting.
• they communicate and co-operate with people or each other, based on a wellgrounded understanding of the objects, events and processes in their environment, and their own situation, competences and knowledge.

Work will result in demonstrators that operate largely autonomously in demanding and open-ended environments which call for a suitable mix of capabilities for sensing, data analysis, processing, control and acting; and for communication and co-operation with people or machines or both. Where required, systems will integrate high-level cognitive competencies; for example, for reasoning, planning and decision-making, and for active environmental modelling.

Proposals satisfying the above requirements should focus on one of the following areas:

• Robots handling, individually or jointly, tangible objects of different shapes and sizes, and operating either fully autonomously (as for instance in difficult terrains with a need for robust locomotion, navigation and obstacle avoidance) or in co-operation with people in complex, dynamic spatial environments (e.g. domestic environments).
• Robots, sensor networks and other artificial systems, monitoring and controlling material and informational processes e.g. in industrial manufacturing or public services domains. This may include information gathering and interpretation in real-time emergency or hazardous situations (e.g. through multi-sensory data-fusion) or in virtual spaces related to real world objects and people.
• Intuitive multimodal interfaces and interpersonal communication systems providing personalised interactivity in real-world and virtual environments, based on improved human interaction modelling and understanding of contextually-referred communication, for example, by signs and signals in all modes (such as sound, vision, touch) and modalities (such as natural language, both spoken and written), through autonomous adaptation and by addressing user needs, intentions and emotions.

Work proposed in any of these areas should, as appropriate:

• develop and apply engineering approaches that cater for real-time requirements (if present) and systems modularity, and ensure the reliability, flexibility, robustness, scalability and, where relevant, also the safety of the resulting systems; and develop criteria for benchmarking these properties;
• contribute to the theory and application of learning in artificial systems, tackling issues related to the purposive and largely autonomous interpretation of sensorgenerated data arising in different environments, and to novel design and implementation principles of pertinent systems architectures.
• explore and validate the use of:
  • advanced sensor, actuator, memory and control elements, components and platforms, based on new, possibly bio-mimetic, materials and hardware designs – e.g. for the realisation of systems with greater structural and functional diversity and modularity
  • new, possibly bio-inspired, information-processing paradigms, and of models of natural cognition (including human mental and linguistic development), adaptation, self-organisation, and emergence; and take account of the role of systems embodiment and affordances.
  • new ways of combining statistical, knowledge driven and cognitive approaches to language understanding, generation, and translation by machines.

A principled approach to structuring research in relevant areas, addressing in particular learning in artificial systems, the requirements for cognitive capacities of robotic, interactive and language support systems, and including the development of experimental scenarios, the development or construction of resources for experimentation, and the development of performance metrics and definitions of autonomy levels for artificial systems.

Co-ordination with related national or regional research programmes or initiatives.