Sciweavers

ATAL
2011
Springer
12 years 11 months ago
Learning action models for multi-agent planning
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...
Hankz Hankui Zhuo, Hector Muñoz-Avila, Qian...
AIPS
2011
13 years 2 months ago
Cross-Domain Action-Model Acquisition for Planning via Web Search
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...
Hankz Hankui Zhuo, Qiang Yang, Rong Pan, Lei Li
JAIR
2008
148views more  JAIR 2008»
13 years 11 months ago
Learning Partially Observable Deterministic Action Models
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...
Eyal Amir, Allen Chang
AI
2007
Springer
13 years 11 months ago
Learning action models from plan examples using weighted MAX-SAT
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...
Qiang Yang, Kangheng Wu, Yunfei Jiang
AIPS
2000
14 years 7 days ago
Probabilistic Hybrid Action Models for Predicting Concurrent Percept-Driven Robot Behavior
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...
Michael Beetz, Henrik Grosskreutz
ATAL
2006
Springer
14 years 2 months ago
Action awareness: enabling agents to optimize, transform, and coordinate plans
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...
Freek Stulp, Michael Beetz
CVPR
2010
IEEE
14 years 4 months ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia