— In this paper, we consider the problem of exploring an unknown environment with a team of mobile robots. One of the key issues in multi-robot exploration is how to assign targe...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Multiagent systems are rapidly finding applications in a variety of domains, including robotics, distributed control, telecommunications, and economics. The complexity of many task...
Inductive Logic Programming (ILP) systems have been successfully applied to solve complex problems in bioinformatics by viewing them as binary classification tasks. It remains an...
Huma Lodhi, Stephen Muggleton, Michael J. E. Stern...
In robotics, recognition of human activity has been used extensively for robot task learning through imitation and demonstration. However, there has not been much work on modeling...
Isabel Serrano Vicente, Ville Kyrki, Danica Kragic...