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» Adaptation of Hierarchical Task Network Plans
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IROS
2007
IEEE
125views Robotics» more  IROS 2007»
14 years 2 months ago
Probabilistic inference for structured planning in robotics
Abstract— Real-world robotic environments are highly structured. The scalability of planning and reasoning methods to cope with complex problems in such environments crucially de...
Marc Toussaint, Christian Goerick
GECCO
2004
Springer
14 years 1 months ago
Evolved Motor Primitives and Sequences in a Hierarchical Recurrent Neural Network
This study describes how complex goal-directed behavior can evolve in a hierarchically organized recurrent neural network controlling a simulated Khepera robot. Different types of ...
Rainer W. Paine, Jun Tani
AINA
2007
IEEE
14 years 2 months ago
OWL-Based Context-Dependent Task Modeling and Deducing
In the near future, homes are envisioned to be equipped with numerous intelligent communicating devices. Such smart home needs to exhibit highly adaptive behavior to meet the inha...
Hongbo Ni, Xingshe Zhou, Zhiwen Yu, Kejian Miao
AIPS
2009
13 years 9 months ago
Learning User Plan Preferences Obfuscated by Feasibility Constraints
It has long been recognized that users can have complex preferences on plans. Non-intrusive learning of such preferences by observing the plans executed by the user is an attracti...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
ICDM
2003
IEEE
119views Data Mining» more  ICDM 2003»
14 years 1 months ago
A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering
Clustering by document concepts is a powerful way of retrieving information from a large number of documents. This task in general does not make any assumption on the data distrib...
Chihli Hung, Stefan Wermter