One player thinks of a secret combination of four distinct colors from the set red (r), orange (o), yellow (y), green (g), blue (b), and violet (v).
The other player must guess a combination of four distinct colors. The first player then indicates how many correct colors are in the correct positions, and how many correct colors are in incorrect positions.
For example, if the secret combination is bryg and the second player guesses bgyv, the first player will respond "2 1" because blue and yellow are in the correct position, and green is in the combination but in the wrong place.
When you start the program with the green flag, you can choose to be the first player, thinking of a secret combination and responding to the computer's guesses (S), or to be the second player and guess the computer's secret combination (G).
If you make every guess count, you should always be able to win in seven guesses!data:image/png;base64,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data:image/png;base64,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1datamapmany1data lists11110i1contcatchtagcontcatchtagTakes a text string as input, and reports a new text string containing all but the first character of the input.resulti2Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the first word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)Takes a text string as input, and reports a new text string containing all but the last letter of the input.resulti1Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the last word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)11111Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing only the first word, with no spaces before or after it.Takes a text string as input, and reports the last character in the string.Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing only the last word of the input, with no spaces before or after it.11Takes a text string as input, and reports TRUE if the string has no characters in it of any kind, otherwise false.Takes a text string as input, and reports TRUE if the input contains no characters other than spaces (therefore, no words when the string is considered as a sentence), otherwise FALSE.Takes a text string as input, and reports a list in which each item is a single character from the string.Reports a new list containing the items of the input list, but in the opposite order.1inputresultReports a new list whose items are the same as in the input list, except that if two or more equal items appear in the input list, only the last one is kept in the result.1Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot. For a list of numbers, using < as the comparison function will sort from low to high; using > will sort from high to low.1even itemsmerge11#1#2Take any number of input lists, and create a new list containing the items of the input lists. So
APPEND [A B] [C D]
where the [,,,] are lists reports the list
[A B C D]
not [[A B] [C D]].111111color#guesses1-18017020wait100#guesses140winroygbvroygroybroyvrogyrogbrogvrobyrobgrobvrovyrovgrovbryogryobryovrygorygbrygvryborybgrybvryvoryvgryvbrgoyrgobrgovrgyorgybrgyvrgborgbyrgbvrgvorgvyrgvbrboyrbogrbovrbyorbygrbyvrbgorbgyrbgvrbvorbvyrbvgrvoyrvogrvobrvyorvygrvybrvgorvgyrvgbrvborvbyrvbgorygoryboryvorgyorgborgvorbyorbgorbvorvyorvgorvboyrgoyrboyrvoygroygboygvoybroybgoybvoyvroyvgoyvbogryogrbogrvogyrogybogyvogbrogbyogbvogvrogvyogvbobryobrgobrvobyrobygobyvobgrobgyobgvobvrobvyobvgovryovrgovrbovyrovygovybovgrovgyovgbovbrovbyovbgyrogyrobyrovyrgoyrgbyrgvyrboyrbgyrbvyrvoyrvgyrvbyorgyorbyorvyogryogbyogvyobryobgyobvyovryovgyovbygroygrbygrvygorygobygovygbrygboygbvygvrygvoygvbybroybrgybrvyborybogybovybgrybgoybgvybvrybvoybvgyvroyvrgyvrbyvoryvogyvobyvgryvgoyvgbyvbryvboyvbggroygrobgrovgryogrybgryvgrbogrbygrbvgrvogrvygrvbgorygorbgorvgoyrgoybgoyvgobrgobygobvgovrgovygovbgyrogyrbgyrvgyorgyobgyovgybrgybogybvgyvrgyvogyvbgbrogbrygbrvgborgboygbovgbyrgbyogbyvgbvrgbvogbvygvrogvrygvrbgvorgvoygvobgvyrgvyogvybgvbrgvbogvbybroybrogbrovbryobrygbryvbrgobrgybrgvbrvobrvybrvgboryborgborvboyrboygboyvbogrbogybogvbovrbovybovgbyrobyrgbyrvbyorbyogbyovbygrbygobygvbyvrbyvobyvgbgrobgrybgrvbgorbgoybgovbgyrbgyobgyvbgvrbgvobgvybvrobvrybvrgbvorbvoybvogbvyrbvyobvygbvgrbvgobvgyvroyvrogvrobvryovrygvrybvrgovrgyvrgbvrbovrbyvrbgvoryvorgvorbvoyrvoygvoybvogrvogyvogbvobrvobyvobgvyrovyrgvyrbvyorvyogvyobvygrvygovygbvybrvybovybgvgrovgryvgrbvgorvgoyvgobvgyrvgyovgybvgbrvgbovgbyvbrovbryvbrgvborvboyvbogvbyrvbyovbygvbgrvbgovbgy