Circuits to control--learning engineering by designing LEGO robots

By storing situation-action pairs, a lazy memory builds an non-explicit model of the situation transition function, that is used as a bias to leverage the model-free

Guaranteed characterization of the explored space of a mobile robot by using subpavings..

Thus we can compute the boundary of the free space of the spider robot in the case where the foothold re- gions are n line segments in O ( jE Aj log n ) time and. O ( jE Aj ( n

For optimization, it was recommended that the second rewrite phase performs chain folding, a generic and well-explored MapReduce design pattern [2, 3, 6, 9].. Chain folding can be

It appears that 94% of the people who worked in groups during the MOOCs prepared the case studies with their team, while the number of people who prepared the

During the talk I will argue that robots interacting with humans in everyday situations, even if motorically and sensorially very skilled and extremely clever in action execution

Inverse Reinforcement Learning method enables a robot to learn a policy using discrete and finite MDP (Markov Decision Process) in which the states are derived from the robot’s

Kajita [Kajita 2003], Nishiwaki [Nishiwaki 2009b] or Naveau [Naveau 2014] also solve the two problems separately but added a Dynamic Filter to take into account the whole-body