• P1. Develop an architecture for Cognitive Agents, including the following sub-systems:
  • S1. Perception
  • S2. Attention Control
  • S3. Goals-oriented Computational Model
  • S4. Learning
  • S5. Goal Generation system
  • S6. Concept System
  • S7. Reasoning system
  • S8. Action Generation system
  • S9. Abstraction
  
  
• P2. Develop further the Abstraction Mechanism to produce concept hierarchies on top of basic concepts.
• P3. Implement the architecture in an embodied robotic agent, which will be tested in a ‘Patrolling, Incident Detection & Tracking Scenario’ in an outdoors environment.

The project’s duration is 36 months. The development of the core components will follow an order from lower level sub-systems to the highest. Figure 1 shows the timeline. Similarly coloured components are closely related.

• M1. Perception Architecture (M06)
• M2. Concept System Architecture (M12)
• M3. Abstraction System Architecture (M18)
• M4. Mobile platform commissioned (M16)
• M5. Initial GNOSYS architecture implemented on mobile platform (M24)
• M6. Final GNOSYS architecture implemented on mobile platform (M32)
• M7. Test-bed and evaluation criteria for architecture assessment (M21)

• I1. Exhibit ‘instinctive’ behaviours and act on them (curiosity, survival).
• I2. Exhibit the generation of alternative virtual plans and selection of realisable plan biased through previous experience.
• I3. Detection of novelties.
• I4. Initiation of learning behaviours for novel environment.
• I5. Creation of automated processing modes and integration with attentive responses. Automated modes represent reactive responses of learned action-sequences for given stimulus. Automated modes are monitored by attention system for response failures.
• I6. Multi-modal perceptual fusion
• I7. Overall fused decision (action generation) generation from competing modalities.
• I8. Concept formation using variable dimension feature vectors.
• I9. Abstraction of concepts and development of concept hierarchies during operation.
• I10. Creation of goals and biasing of attention.
• I11. Development of value systems, emotional states and implementation of internal drives.
• I12. Development of sensory and motor attention per modality.
• I13. Development of computational model which prioritises responses based on global attention competition, internal drives/value systems and projected agent states.
• I14. Integration of user-level goals with own goals. User-level goals change priority depending on the observed external and internal states and other competing goals.