1. CSI 661 - Uncertainty in A.I. Lecture 91

2. 2

3. 3 Three Main Approaches To Approximate Inference MCMC Variational Methods Loopy belief propagation

4. CSI 661 - Uncertainty in A.I. Lecture 94 Decision Making With BNets

5. CSI 661 - Uncertainty in A.I. Lecture 95 Minimize Risk

6. CSI 661 - Uncertainty in A.I. Lecture 96 Influence Diagrams

7. CSI 661 - Uncertainty in A.I. Lecture 97 Putting a Price on Information

8. CSI 661 - Uncertainty in A.I. Lecture 98 Improvement With Extra Link

9. CSI 661 - Uncertainty in A.I. Lecture 99 Dynamic Belief Networks

10. CSI 661 - Uncertainty in A.I. Lecture 910 DBNet

11. CSI 661 - Uncertainty in A.I. Lecture 911 HMM Algorithms Applied to DBNET

12. CSI 661 - Uncertainty in A.I. Lecture 912 Next Lecture Major criticism of BNets as models of human behavior Learning Bayes Nets –Parameter estimation –Learning structure