In this paper, we outline a framework for the development of natural language interfaces to agent systems with a focus on action representation. The architecture comprises a natur...
This paper addresses the problem of activity recognition for physically-embodied agent teams. We define team activity recognition as the process of identifying team behaviors from...
Research in learning and planning in real-time strategy (RTS) games is very interesting in several industries such as military industry, robotics, and most importantly game industr...
Ibrahim Fathy, Mostafa Aref, Omar Enayet, Abdelrah...
The Mobile Agents model-based, distributed architecture, which integrates diverse components in a system for lunar and planetary surface operations, was extensively tested in a tw...
William J. Clancey, Maarten Sierhuis, Rich Alena, ...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...