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» Applying causal inference to understand emergent behavior
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WSC
2008
13 years 7 months ago
Applying causal inference to understand emergent behavior
Emergent behaviors in simulations require explanation, so that valid behaviors can be separated from design or coding errors. Validation of emergent behavior requires accumulation...
Ross Gore, Paul F. Reynolds Jr.
IUI
2003
ACM
13 years 10 months ago
Inferring user goals from personality and behavior in a causal model of user affect
We present a probabilistic model, based on Dynamic Decision Networks, to assess user affect from possible causes of emotional arousal. The model relies on the OCC cognitive theory...
Xiaoming Zhou, Cristina Conati
PR
2008
124views more  PR 2008»
13 years 4 months ago
A daily behavior enabled hidden Markov model for human behavior understanding
This paper presents a Hierarchical Context Hidden Markov Model (HC-HMM) for behavior understanding from video streams in a nursing center. The proposed HC-HMM infers elderly behav...
Pau-Choo Chung, Chin-De Liu
MLDM
2009
Springer
13 years 11 months ago
An Evidence-Driven Probabilistic Inference Framework for Semantic Image Understanding
This work presents an image analysis framework driven by emerging evidence and constrained by the semantics expressed in an ontology. Human perception, apart from visual stimulus a...
Spiros Nikolopoulos, Georgios Th. Papadopoulos, Io...
HICSS
2003
IEEE
116views Biometrics» more  HICSS 2003»
13 years 10 months ago
Modeling Instrumental Conditioning - The Behavioral Regulation Approach
Basically, instrumental conditioning is learning through consequences: Behavior that produces positive results (high “instrumental response”) is reinforced, and that which pro...
Jose J. Gonzalez, Agata Sawicka