ATAL
2011
Springer
12 years 11 months ago
2011
Springer
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
AIPS
2011
13 years 3 months ago
2011
Applying learning techniques to acquire action models is an area of intense research interest. Most previous works in this area have assumed that there is a significant amount of...
JAIR
2008
13 years 11 months ago
2008
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
AI
2007
Springer
13 years 11 months ago
2007
Springer
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
AIPS
2000
14 years 24 days ago
2000
This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHA...
ATAL
2006
Springer
14 years 3 months ago
2006
Springer
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 adapti...
CVPR
2010
IEEE
14 years 5 months ago
2010
IEEE
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...