Remembering / Forgeting
" Forgeting is important to keep things relevant and fresh. It allows to speed out the process and save memory
Memory = Word Bank
Different levels of memory ->
* Fresh Memory ( quick access memory )
* Permanent Memory ( Hard to forget )
* Temporary Memory ( Cash memory, it needs more re-inforcement to become permanent )
* Bare Memory ( Incomplete, briefly touched; it may dissapear at any moment if not confirmed )
* Forgotten: dumped( Is there, but it won't retrive unless a significan part is re-activated or re-learned );
Frequency: Level of frequency depends on the number of times a word has been detected within a period of time.
The greatest the frequency, the easier to retrive the word and higher chances to remain on permanent memory.
Every word needs a word id and frequency. The application needs a time listener to determine the frequency.
Freshness: The time past since the word was last detected. Every word is kept at the top of "Fresh Memory" everytime is detected.
When a new one is detected, the word past to the second placement in priority or freshness.
* Divide total list by 4 ( 4 stages of memory)
result is the number of placements within each memory
placements = Num_items / 4
FRESHNESS =
Lenght: Shorter words are easily retained in the Permanent memory than long words. Long words need more exposition in order to be
remembered.
Defined by the number of characters.
(int) L = NUM_OF_CHARACTERS * (-1) // To keep the number low and favor less over more.
Intensity: Words matching with objectives ( Grade System ) are more relevant to purpose, and therefore more desirables. The have
presedence over non matching words.
* Relevance shows intensity: Intensity could be either positive or negative. In this case, shallow takes the back seat.
* Hight intensity words will be remembered either positive or negative. This will change the personality of the Bot.
* The more possitive feedback, the nicer Bot we will have, the more negative, the most evil the Bot.
For the purpose of WORD_RECORDING_VALUE, Relevance turns into a positive number;
WORD_RECORDING_VALUE = FREQUENCY + FRESHNESS + LENGHT + INTENSITY
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