This paper proposes a unique map learning method for mobile robots based on the co-visibility infor mation of objects i.e., the information on whether two objects are visible at...
We present an expressive agent design language for reinforcement learning that allows the user to constrain the policies considered by the learning process.The language includes s...
— Legged robots represent great promise for transport in unstructured environments. However, it has been difficult to devise motion planning strategies that achieve a combinatio...
The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments. A typical example is a case of RoboCup...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...