simplest ai trick gdc2013 dino v2 (1)
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Simplest AI Trick in the BookNormalised 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
Abstract away the device dependent positional values
(0 to 255? -1024 to 1024?) and normalise.
Normalised values are much easier to work with.
-1 10
Example:Analog Input - Left / Right Rotation
Input Device
1024
-1024
Movement Driver
1
-1
RotationDegrees per
Frame
Normalizer
5
-5
Example:Analog Input - Left / Right Rotation
Input Device
1024
-1024
Movement Driver
1
-1
RotationDegrees per
Frame
Normalizer
5
-5
Linear relationship
Degrees rotation per frame
Control input (left - right)
Linear relationship
Degrees rotation per frame
Control input (left - right)
I want greater sensitivity
Linear relationship
Degrees rotation per frame
Control input (left - right)
Linear relationship
Degrees rotation per frame
Control input (left - right)
I also want full range
Linear relationship
Degrees rotation per frame
Control input (left - right)
Greater sensitivity
Full Range
Example:Analog Input - Left / Right Rotation
Input Device
1024
-1024
Movement Driver
1
-1
RotationDegrees per
Frame
Normalizer
5
-5
Sigmoid like
function
1
-1
Example:Analog Input - Left / Right Rotation
Input Device
1024
-1024
Movement Driver
1
-1
RotationDegrees per
Frame
Normalizer
5
-5
Sigmoid like
function
1
-1
k
Sigmoid function?
Logit function?
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