Technical University of Munich

@inproceedings{stulp_action_2006,
 author = {F Stulp and M Beetz},
 title = {Action Awareness – Enabling Agents to Optimize, Transform, and Coordinate
	Plans},
 booktitle = {Proceedings of the Fifth International Joint Conference on Autonomous
	Agents and Multiagent Systems ({AAMAS)}},
 year = {2006},
 abstract = {As agent systems are solving more and more complex tasks in increasingly
	challenging domains, the systems themselves are becoming more complex
	too, often compromising their adaptivity and robustness. A promising
	approach to solve this problem is to provide agents with reflective
	capabilities. Agents that can reflect on the effects and expected
	performance of their actions, are more aware and knowledgeable of
	their capabilities and shortcomings. In this paper, we introduce
	a computational model for what we call {\textbackslash}emphaction
	awareness. To achieve this awareness, agents learn predictive action
	models from observed experience. This knowledge is then used to optimize,
	transform and coordinate plans. We apply this computational model
	to a number of typical scenarios from robotic soccer. Various experiments
	on real robots demonstrate that action awareness enables the robots
	to improve the performance of their plans substantially.},
}