SOURCE-LINKED INTELLIGENCE

INteractive robots that intuitiVely lEarn to inVErt tasks by ReaSoning about their Execution

CORDIS · observation · Publication date unknown

INteractive robots that intuitiVely lEarn to inVErt tasks by ReaSoning about their Execution Despite the impressive advancements in Artificial Intelligence (AI), current robotic solutions fall short of the expectations when they are requested to operate in partially unknown environments. Most of all, robots lack the cognitive capabilities to understand a task to the point of being able to perform it in a different domain. As humans, during the learning process we gain deep insights on the execution of a process, which allows us to replicate its execution in a different domain with a little effort. We are also able to invert the task execution and to react to contingencies, by focusing the attention to the most critical prediction phases. However, replicating these cognitive processes in AI-driven robots is challenging as it needs a profound rethinking of the robot learning paradigm itself. The robot needs to understand how to act and imagine, like humans do, the possible consequences of its actions in another domain.

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recordType

award

status

SIGNED

region

EU

value

7999873.5

unit

EUR