As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
This work presents a new algorithm, called Heuristically Accelerated Minimax-Q (HAMMQ), that allows the use of heuristics to speed up the wellknown Multiagent Reinforcement Learni...
Reinaldo A. C. Bianchi, Carlos H. C. Ribeiro, Anna...
— We describe a simple and intuitive policy gradient method for improving parametrized quadrocopter multi-flips by combining iterative experiments with information from a first...
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...