Compressing real-time input through bandwidth constrained connections has been studied within robotics, wireless sensor networks, and image processing. When there are bandwidth con...
Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g.,...
Social insects provide us with a powerful metaphor to create decentralized systems of simple interacting, and often mobile, agents. The emergent collective intelligence of social i...
Eric Bonabeau, Andrej Sobkowski, Guy Theraulaz, Je...
Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent’s limited computational resources to achieve a good estimate of the value of ...
This paper discusses the emergence of sensorimotor coordination for ESCHeR, a 4DOF redundant foveated robot-head, by interaction with its environment. A feedback-error-learning(FEL...