Behavioral research suggests that human learning in some multi-agent systems can be predicted with surprisingly simple “foresight-free” models. The current note discusses the ...
The paper presents a new technique for extracting symbolic ground facts out of the sensor data stream in autonomous robots for use under hybrid control architectures, which compris...
The computational grounding problem – the gap between the mental models of an agent and its computational model – is a well known problem within the agent research community. ...
Symbolic reasoning is a well understood and effective approach to handling reasoning over formally represented knowledge; however, simple symbolic inference systems necessarily sl...
Matthew E. Taylor, Cynthia Matuszek, Pace Reagan S...
Solving real-world problems using symbolic planning often requires a simplified formulation of the original problem, since certain subproblems cannot be represented at all or only...
Christian Dornhege, Patrick Eyerich, Thomas Keller...