1-4-26-30-31
4-8-17-28-30
4-13-19-30-34
1-2-4-28-36
5-6-10-17-33-won $2
11-17-18-33-34
4-17-20-23-33
5-14-15-17-34
5-17-19-23-31
Wednesday, January 13, 2010
How did we do in Cash Five on 12 January 2009?
Tuesday, January 12, 2010
Some Texas Cash Five picks for 12 January 2010
1-4-26-30-31
4-8-17-28-30
4-13-19-30-34
1-2-4-28-36
5-6-10-17-33
11-17-18-33-34
4-17-20-23-33
5-14-15-17-34
5-17-19-23-31
There are no guarantees here. You take your chances. I will report how they do after tonight's game, just for fun.
Monday, January 11, 2010
How about some Mega Millions picks for 12 January 2010?
Pick Mega Ball
15-18-39-40-45 6
11-13-18-28-48 39
7-18-28-41-50 36
8-18-28-37-55 15
8-13-28-39-41 44
4-22-27-39-46 23
22-27-39-43-46 46
4-27-43-46-55 40
8-18-44-48-56 27
1- 6-31-53-54 27
1-27-45-50-53 2
6-15-45-53-55 24
How we did in Cash Five for 11 January 2010
(January 11, 2010):
8-14-19-23-28
11-14-19-24-32 - won $2
8-10-14-16-33
6-10-14-24-37
3-13-15-19-33
3-16-19-23-24
3-17-19-28-32
6-13-16-19-28
What I have been doing since August 2009
8-14-19-23-28
11-14-19-24-32
8-10-14-16-33
6-10-14-24-37
3-13-15-19-33
3-16-19-23-24
3-17-19-28-32
6-13-16-19-28
This week, I am mostly playing on paper, not actually spending money buying picks. I would not recommend buying these, but it would be interesting to see how these perform in tonight's Cash Five drawing. I will give an update and some picks for tmorrow night's game tomorrow.
Saturday, November 21, 2009
The CRU documents are posted to a news group
Wednesday, October 28, 2009
Artificial Intelligence in Action
The emphasis on rule-based systems in the mid-1980's was a mistaken notion based on experience with mostly toy systems. The work of John R. Anderson was the exception. He continued to evolve tutoring systems that worked off a combination of rules and knowledge structures.
I have been working on programs since August that use some alternate approaches to applying AI techniques. The classic architecture of "generate and test" still works. The major component of the "generate" portion are heuristic rating systems and some just plain "hacks". I quickly found that in my problem domain of choice, that I had to go beyond principles and look at performance with real world data. In conjunction with the heuristic rating systems, I also use some extremely simple machine learning. Those two together seem to be producing adequate performance. I will continue to tweak and test every day, as new ideas occur to me and I see the results of applying what I have.