The general goal of the Mind RACES project is to investigate different anticipatory cognitive mechanisms and architectures in order to build Cognitive Systems endowed with the ability to predict the outcome of their actions, to build a model of future events, to control their perception anticipating future stimuli and to emotionally react to possible future scenarios. Such Anticipatory Cognitive Systems will contribute to the successful implementation of the desired ambient intelligence.

To match this general goal the project has identified four distinct objectives which correspond to four different phases in the project.

On the basis of specific smart environments and multi-robot scenarios, the project


• will identify typologies of problems in three cognitive functions sets (attention monitoring and control; goal directed behaviour, pro-activity and analogy; anticipatory emotions) which require different anticipatory cognitive capabilities. The project
• will improve existing anticipatory architectures and will incorporate missing anticipatory functionalities in them. The performances of these architectures will be tested in the previously identified scenarios. In order to highlight relative strengths and weaknesses, the project
• will compare in the same scenarios anticipatory architectures implemented from different theoretical background. In this phase we have the opportunity of evaluating if the translation of some mechanisms in other implementations show a different performance or if it leads to new side effects (that we can possibly exploit). This approach privileges (as in all the project) the cognitive function set over the concrete implementation and will give a relevant contribute to the theoretical foundation of the mechanisms, extracting the conceptual core from the constraints of the single implementations. At the same time, this leads us to the next phase. Finally, the project
• will design, implement and test in the scenarios the cognitive architectures that integrate anticipatory mechanisms from different cognitive function sets. Simulations and real robots will be used both to improve and compare single anticipatory models and to integrate them in the same cognitive architectures.