Modeling and inference with relational dynamic bayesian networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5549 LNAI, Issue , 2009, Pages 287-290

  Manfredotti, Cristina ^a,b  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DYNAMIC BAYESIAN NETWORK; DYNAMIC DOMAINS; EXPLICIT RECOGNITION; MULTI AGENT; PARTICLE FILTER ALGORITHMS; STRATEGIC ANALYSIS; TERRORIST ACTIVITIES; TRAFFIC MONITORING; TRANSITION MODEL;

ARTIFICIAL INTELLIGENCE; DISTRIBUTED PARAMETER NETWORKS; INFERENCE ENGINES; INTELLIGENT NETWORKS; KNOWLEDGE BASED SYSTEMS; MOTOR TRANSPORTATION;

BAYESIAN NETWORKS;

EID: 69849083395     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01818-3_44     Document Type: Conference Paper

References (3)

1. Arulampalam, S., Maskell, S., Gordon, N.: A tutorial on particle filters for online nonlinear/non-gaussian bayesian tracking. IEEE Transactions on Signal Processing 50, 174-188 (2002
2. Friedman, N., Getoor, L., Koller, D., Pfeffer, A.: Learning probabilistic relational models. In: IJCAI, pp. 1300-1309 (1999
3. Milch, B., Russell, S.J.: General-purpose mcmc inference over relational structures. In: UAI (2006