WhiteICE version information
WhiteICE v1.42b (in development)
TODO: try different settings and configurations to increase performance measurements (need better results).
WhiteICE v1.41b (most recent)
DONE: There is a bug in the code that causes windows GUI version of the software to crash in random locations. Lots of debugging needed: fixed many small bugs until error was found. Software should now be more stable.
DONE: implement —lsl-stream-name=<string> to make it possible to read non-standard stream.
DONE: fixing bugs created by ChatGPT fixing "bugs".
DONE: test shorter stimulation lengths again. (500msecs/250msecs) => don't work well, back to (5000msecs/2500msecs).
DONE: testing (minor fixes in reinforcement learning code done) [lsl concentration channels=4 and lsl intelligence channels=8 (not tested)] => one 149min concentration run gave -0.37% results - need to try to get performance fixed (change tau=0.1 to tau=0.2, deepness=3 to deepness=5 => lsl concentration run gave 2.7% effect and positive average change => seems to work a bit)
DONE: try to set forgetting time to 30 minutes so only recent response-measurements have effect to reinforcement model????
WhiteICE v1.40b
Added variances of target terms to RL model data. Now results are about same when neural network's width=64 with "lsl fft concentration" target than before 3-5% effect and positive effects otherwise too. This is enough for v1.40b. TODO: but still need test with "lsl fft intelligence eeg_channels=8" target to see if the most important target increases.
Increased forgetting time from one hour to three hours so more data is available for optimization.
DONE: fixed "--save-video" to be faster (worse compression) and not to run out of memory for buffering video frames for encoding.
WhiteICE v1.39b
New version with improved RL algorithm that SHOULD give more often positive results (in many hours long stimulation). Stimulation interval is 1000ms. Effect seem to be only about 1% with this new code.
Program learns very slowly, 3h 20minutes (300 models) didn’t show big improvements. Try to increase tau from 0.02 to 0.1 and see if it still increases performance a bit. => tau increase seem to give worse results???
Added forgetting to reinforcemen learning, now 30 minutes older measurements are not used. TODO: increase tau from 0.02 to 0.1 (for testing) so model can learn temporal dynamics better.
DONE: Added additional measurements to RL's state vector.
NOW: 5000 msecs stimulation time seems to give much better results than 1000 ms (2-3% effect). However, forgetting time should be maybe increased from 30minutes to 60minutes? (TODO: test it) AND test 10 sec long stimulus again to see if there is better effect (+3.1% effect vs random and about zero effect to distance).
FINAL: 5000 msecs stimulation time which often gives 3% result. Note that this is worse than in 1.38b which seem to give 5% result but RL algorithms in 1.39 are more sophisticated.
WhiteICE v1.38b
This version re-enabled longer stimulation interval 5000ms which seem to have positive effect to "episodes-result.txt" average reinforcement value time-series when stimulatio is run for many hours. Typical effect seem to be 5% (versus random stimulation)
WhiteICE v1.37b
This experimental version used very short stimulation interval 500ms.