Craig Innes

Computer Science

1. Decision Problem 100%
2. Markov Decision Process 66%
3. Temporal Logic 55%
4. Importance Sampling 55%
5. Programming Language 50%
6. And-States 44%
7. Proposal Distribution 44%
8. Simulation Mode 33%
9. Specification Language 33%
10. Sampling Technique 33%
11. Automatic Synthesis 33%
12. path-planning 33%
13. State Estimate 33%
14. Fast Convergence 33%
15. Feedback Control 33%
16. Sensor Measurement 33%
17. Learning Algorithm 33%
18. Autonomous System 33%
19. Soft Robotics 33%
20. Training Data 33%
21. Driven Approach 33%
22. Linear Temporal Logic 33%
23. Actuator 33%
24. Black-Box Testing 33%
25. Case Study 33%
26. Complex Process 33%
27. Finite Element Analysis 26%
28. Autonomous Vehicles 22%
29. Reinforcement Learning 16%
30. Training Environment 16%
31. Training Policy 16%
32. Deployment Environment 16%
33. Training Phase 16%
34. Structured Model 16%
35. Testing Condition 16%
36. Decision-Making 16%
37. Continuous Control 16%
38. Generative Model 16%
39. Inverse Problem 16%
40. Medical Imaging 16%
41. Influence Diagram 16%
42. Exhaustive Testing 16%
43. Data Augmentation 16%
44. New-State 11%
45. Tacit Assumption 11%
46. Hazard Analysis Technique 11%
47. Side Simulation 11%
48. Change Scenario 11%
49. Design Experiment 6%
50. Computational Complexity 6%