TY  - BOOK
AU  - Krauthausen, Peter
AB  - This thesis is concerned with intention recognition for a humanoid robot and investigates how the challenges of uncertain and incomplete observations, a high degree of detail of the used models, and real-time inference may be addressed by modeling the human rationale as hybrid, dynamic Bayesian networks and performing inference with these models. The key focus lies on the automatic identification of the employed nonlinear stochastic dependencies and the situation-specific inference.
DO  - 10.5445/KSP/1000031356
ID  - OAPEN ID: 34486
KW  - Intention Recognition
KW  - Dynamic Systems
KW  - (Conditional) Density Estimation
KW  - Regularization
KW  - Human-Robot-Cooperation
L1  - https://www.ksp.kit.edu/9783866449527
LA  - English
LK  - https://directory.doabooks.org/handle/20.500.12854/51483
PB  - KIT Scientific Publishing
PY  - 2013
SN  - 9783866449527
TI  - Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperationnull
ER  - 
