Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...
The human neural responses associated with cognitive events, referred as event related potentials (ERPs), can provide reliable inference for target image detection. Incremental le...
Yonghong Huang, Deniz Erdogmus, Misha Pavel, Kenne...
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
Many multiagent problems comprise subtasks which can be considered as reinforcement learning (RL) problems. In addition to classical temporal difference methods, evolutionary algo...
Jan Hendrik Metzen, Mark Edgington, Yohannes Kassa...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...