Simplest ai trick gdc2013 dino v2 (1)

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This document discusses normalizing analog input values and using a normalized tunable sigmoid function to map the normalized values to control outputs. It explains that normalizing input values between -1 and 1 makes them easier to work with for tasks like control systems. An example is given of normalizing left/right rotation input between -1024 to 1024 to -1 to 1. A sigmoid-like function is then used to scale the normalized input to degrees of rotation per frame in a way that provides both full range of control and sensitivity, with the steepness adjustable via a tunable k parameter.

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Simplest AI Trick in the Book
Normalised Tunable Sigmoid Function

Dino Dini NHTV University of Applied Sciences

Normalized Values Are Useful
For example:

● Utility calculations
● Input management
● Control systems
● Tunable parameters

Analog Input

-1 0 1
Abstract away the device dependent positional values
(0 to 255? -1024 to 1024?) and normalise.

Normalised values are much easier to work with.

Example:
Analog Input - Left / Right Rotation

Input 1024 1
Normalizer
Device -1024 -1

Movement 5 Rotation
Degrees per
Driver -5 Frame

Linear relationship
Degrees rotation per frame

Control input (left - right)

Linear relationship
Degrees rotation per frame

I want greater sensitivity

Control input (left - right)

Linear relationship
Degrees rotation per frame
I also want full range

Control input (left - right)

Linear relationship
Degrees rotation per frame
Full Range

Greater sensitivity

Control input (left - right)

Example:
Analog Input - Left / Right Rotation

Input 1024 1
Normalizer
Device -1024 -1

Sigmoid 1 5 Rotation
Movement
like Degrees per
-1 Driver -5
function Frame

Normalised Tunable (half) Sigmoid
Function?

Normalised Tunable (half) Sigmoid
Function?

k = 0.2

Normalised Tunable (half) Sigmoid
Function?

k = 0.01

Normalised Tunable (half) Sigmoid
Function?

k=2

Normalised Tunable (half) Sigmoid
Function?

k = -1.2

Normalised Tunable (half) Sigmoid
Function?

k = -1.01

Normalised Tunable (half) Sigmoid
Function?

k = -3

Normalised Tunable Sigmoid Function

k = 0.2

Normalised Tunable Sigmoid Function

Thank you

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Simplest ai trick gdc2013 dino v2 (1)

1. Simplest AI Trick in the Book Normalised Tunable Sigmoid Function Dino Dini NHTV University of Applied Sciences

2. Normalized Values Are Useful For example: ● Utility calculations ● Input management ● Control systems ● Tunable parameters

3. Analog Input -1 0 1 Abstract away the device dependent positional values (0 to 255? -1024 to 1024?) and normalise. Normalised values are much easier to work with.

4. Example: Analog Input - Left / Right Rotation Input 1024 1 Normalizer Device -1024 -1 Movement 5 Rotation Degrees per Driver -5 Frame

5. Example: Analog Input - Left / Right Rotation Input 1024 1 Normalizer Device -1024 -1 Movement 5 Rotation Degrees per Driver -5 Frame

6. Linear relationship Degrees rotation per frame Control input (left - right)

7. Linear relationship Degrees rotation per frame I want greater sensitivity Control input (left - right)

8. Linear relationship Degrees rotation per frame Control input (left - right)

9. Linear relationship Degrees rotation per frame I also want full range Control input (left - right)

10. Linear relationship Degrees rotation per frame Full Range Greater sensitivity Control input (left - right)

11. Example: Analog Input - Left / Right Rotation Input 1024 1 Normalizer Device -1024 -1 Sigmoid 1 5 Rotation Movement like Degrees per -1 Driver -5 function Frame

12. Example: Analog Input - Left / Right Rotation Input 1024 1 Normalizer Device -1024 -1 Sigmoid 1 5 Rotation Movement like Degrees per -1 Driver -5 function Frame k

13. Sigmoid function?

14. Logit function?

15. Normalised Tunable (half) Sigmoid Function?

16. Normalised Tunable (half) Sigmoid Function? k = 0.2

17. Normalised Tunable (half) Sigmoid Function? k = 0.01

18. Normalised Tunable (half) Sigmoid Function? k=2

19. Normalised Tunable (half) Sigmoid Function? k = -1.2

20. Normalised Tunable (half) Sigmoid Function? k = -1.01

21. Normalised Tunable (half) Sigmoid Function? k = -3

22. Normalised Tunable Sigmoid Function k = 0.2

23. Normalised Tunable Sigmoid Function Thank you

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Simplest ai trick gdc2013 dino v2 (1)

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