Methods for making collective decisions independent of irrelevant alternatives

• US 20090138422A1
• Filed: 11/23/2007
• Published: 05/28/2009
• Est. Priority Date: 11/23/2007
• Status: Abandoned Application

• Current Assignee: Amir Hassan Ghaseminejad Tafreshi
• Original Assignee: Amir Hassan Ghaseminejad Tafreshi
• Inventors: Ghaseminejad Tafreshi, Amir Hassan
• Application Number:
  US11/944,585
• Publication Number:
  US 20090138422A1
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

Methods for making collective decisions independent of irrelevant alternatives. A preferred alternative found, using weighted preference lists while restricting the impact of spoilers, is considered as Independent Collective Choice. If a list is required, it is added to an ordered list of Independent Collective Choices and removed from weighted lists, and finding, adding, and removing are repeated. When selection of a plurality of alternatives with proportional representation is required, the lowest ranked alternative in an Independent Collective Choice Ordered List is removed to find the alternatives with predetermined quota. Some embodiments apply collective choice procedures repeatedly to select the highest ranked alternative, compare the outcomes before and after the removal of alternative combinations, and use the selection of Independent Collective Choice recursively and iteratively when selecting highest or lowest ranked alternatives. Various embodiments can be in decision making systems including humans and machines for selection, sorting, and prediction problems.

Claims

1. A method for making collective decisions, using a given set of weighted preference lists, comprising the steps of:

(a) finding a preferred collective choice using given weighted preference lists while restricting the impact of spoilers and considering said choice as an independent collective choice;

(b) if an ordered list of independent collective choices should be produced, adding said independent collective choice as the next choice to the desired independent collective choice ordered list for given weighted preference lists, otherwise, concluding the decision process with said independent collective choice as decision outcome;

(c) if more alternatives should be selected performing the following steps;

(i.) deleting said independent collective choice from said given weighted preference lists;

(ii.) repeating steps (a) to (c) until at least one of, but not limited to, the following happens;

a predetermined number of collective preferences are selected,

a deadline has passed,

a decision is made,

a task is accomplished,

all the alternatives have been deleted from said given weighted preference lists.

2. The method in claim 1, further comprising the following step at the beginning of the process before step (a):

if the weight of one of the lists in given weighted preference lists, is greater than half of the total sum of weights of said given weighted preference lists, considering said list as the independent collective choice ordered list and its top choice as the independent collective choice and concluding the process, otherwise, continuing with step (a).

3. The method in claim 1, wherein finding a preferred collective choice using given weighted preference lists while restricting the impact of spoilers comprises the steps of:

(a) finding a highest ranked alternative, called strong alternative, using a copy of said given weighted preference lists excluding the spoilers signed in this process;

(b) creating a new list of spoilers using said given weighted preference lists excluding the spoilers signed in this process;

(c) if no spoilers are in the list of spoilers performing the following steps;

(i.) clearing the signs added in this process to said given weighted preference lists;

(ii.) concluding this process with the desired preferred collective choice being the last strong alternative just found in step (a);

(d) if any spoiler is in said list of spoilers, signing at least one spoiler out of said given weighted preference lists;

(e) repeating steps (a) to (e).

4. The method in claim 3, wherein finding a highest ranked alternative and making a ranked list of alternatives using provided copy of weighted preference lists comprise applying one or more methods selected from the group consisting of but not limited to:

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method.

5. The method in claim 3, wherein finding a highest ranked alternative using a provided copy of weighted preference lists comprises the steps of:

(a) finding a remaining alternative by repeatedly removing the highest ranked alternative by repeatedly applying a collective choice procedure;

(b) erasing said remaining alternative from said provided weighted preference lists;

(c) repeating steps (a) to (c) until said provided copy of weighted preference lists has no alternatives;

(d) Considering the last alternative erased as the highest ranked alternative.

6. The method in claim 5, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) finding the highest ranked alternative in said operational copy of weighted preference lists by applying a collective choice procedure selected from the group consisting of but not limited to;

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method;

(ii.) removing said highest ranked alternative from said operational copy of weighted preference lists;

7. The method in claim 5, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) selecting the first choice of each preference list in said operational copy of weighted preference lists;

(ii.) for each first choice selected, summing the weight of said weighted preference lists that have said first choice;

(iii.) selecting the alternative with the highest aggregated weight among said first choices;

(iv.) removing said highest ranked alternative from said operational copy of weighted preference lists.

8. The method in claim 5, further comprising a step to make a ranked list of alternatives performing the following after step (a):

adding said remaining alternative, as the highest ranked alternative so far, to the intended ranked list of alternatives.

9. The method in claim 3, wherein creating a new list of spoilers comprises the steps of:

(a) setting a level-indicator to 1;

(b) concluding the creation of said list of spoilers if at least one of, but not limited to, the following happens;

(i.) the level-indicator is greater than “

the number of alternatives in given weighted preference lists, that are not signed”

minus 2,

(ii.) the level indicator is more than a predetermined level,

(iii.) a deadline has reached;

(c) selecting a new combination of alternatives, from alternatives in “

given weighted preference lists excluding;

the signed alternatives, said strong alternative, spoilers and spoiler combinations in list of spoilers”

, wherein the number of alternatives in the combination is the value of level-indicator;

(d) finding the highest ranked alternative using a copy of said given weighted preference lists without said selected combination of alternatives and without signed alternatives, by applying the same technique used in finding said strong alternative;

(e) if the highest ranked alternative found in step (d) is different than said strong alternative, adding said combination to the anticipated list of spoilers;

(f) If all valid combinations of alternatives at said level-indicator have not been tested, repeating the steps (c) to (f);

(g) incrementing said level-indicator by one;

(h) repeating steps (b) to (h).

10. The method in claim 3, wherein signing at least one spoiler out of said given weighted preference lists comprises the steps of:

(a) creating a sorted list of spoilers by applying one of methods selected from the group consisting of but not limited to;

(i.) recursively employing said steps of claim 1 to produce an independent collective choice ordered list using a copy of said given weighted preference lists including only the alternatives in said list of spoilers, and

(ii.) making a ranked list of alternatives using a copy of said given weighted preference lists including only the alternatives in said list of spoilers;

(b) signing the spoilers out of said given weighted preference lists by performing one or more methods selected from the group consisting of but not limited to;

(i.) signing at least one of spoilers in the list of spoilers out of said given weighted preference lists,

(ii.) signing the lowest ranked alternative in said sorted list of spoilers out of said given weighted preference lists,

(iii.) signing the alternatives of a combination that one of the members of the combination is the lowest ranked alternative in said sorted list of spoilers out of said given weighted preference lists, and

(iv.) signing a plurality of spoilers in said sorted list of spoilers out of said given weighted preference lists.

11. The method in claim 1, wherein finding a preferred collective choice using given weighted preference lists while restricting the impact of spoilers comprises the steps of:

(a) creating a replica of given weighted preference lists;

(b) finding a highest ranked alternative, called strong alternative, using a copy of said replica of weighted preference lists;

(c) creating a new list of spoilers using said replica of weighted preference lists;

(d) if no spoilers are in the list of spoilers concluding this process with the desired preferred collective choice being the last strong alternative just found in step (b);

(e) if any spoiler is in said list of spoilers, removing at least one spoiler out of said replica of weighted preference lists;

(f) repeating steps (b) to (f);

12. The method in claim 11, wherein finding a highest ranked alternative and making a ranked list of alternatives using provided copy of weighted preference lists comprise applying one or more methods selected from the group consisting of but not limited to:

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method.

13. The method in claim 11, wherein finding a highest ranked alternative using a provided copy of weighted preference lists comprises the steps of:

(a) finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure;

(b) erasing said remaining alternative from said provided weighted preference lists;

(c) repeating steps (a) to (c) until said provided copy of weighted preference lists has no alternatives;

(d) Considering the last alternative erased as the highest ranked alternative.

14. The method in claim 13, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) finding the highest ranked alternative in said operational copy of weighted preference lists by applying a collective choice procedure selected from the group consisting of but not limited to;

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method;

(ii.) removing said highest ranked alternative from said operational copy of weighted preference lists;

15. The method in claim 13, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) selecting the first choice of each preference list in said operational copy of weighted preference lists;

(ii.) for each first choice selected, summing the weight of said weighted preference lists that have said first choice;

(iii.) selecting the alternative with the highest aggregated weight among said first choices;

(iv.) removing said highest ranked alternative from said operational copy of weighted preference lists.

16. The method in claim 13, further comprising a step to make a ranked list of alternatives performing the following after step (a):

adding said remaining alternative, as the highest ranked alternative so far, to the intended ranked list of alternatives.

17. The method in claim 11, wherein creating a new list of spoilers comprises the steps of:

(a) setting a level-indicator to 1;

(b) concluding the creation of said list of spoilers if at least one of, but not limited to, the following happens;

(i.) the level-indicator is greater than “

the number of alternatives in supplied weighted preference lists”

minus 2,

(ii.) the level indicator is more than a predetermined level,

(iii.) a deadline has reached;

(c) selecting a new combination of alternatives, from alternatives in “

supplied weighted preference lists excluding said strong alternative, spoilers, and spoiler combinations in list of spoilers”

, wherein the number of alternatives in the combination is the value of level-indicator;

(d) finding the highest ranked alternative using a copy of said supplied weighted preference lists without said selected combination of alternatives, by applying the same technique used in finding said strong alternative;

(e) if the highest ranked alternative found in step (d) is different than said strong alternative, adding said combination to the anticipated list of spoilers;

(f) If all valid combinations of alternatives at said level-indicator have not been tested, repeating the steps (c) to (f);

(g) incrementing said level-indicator by one;

(h) repeating steps (b) to (h).

18. The method in claim 11, wherein removing at least one spoiler out of said replica of weighted preference lists comprises the steps of:

(a) creating a sorted list of spoilers by applying one of methods selected from the group consisting of but not limited to;

(i.) recursively employing said steps of claim 1 to produce an independent collective choice ordered list using a copy of said weighted preference lists including only the alternatives in said list of spoilers, and

(ii.) making a ranked list of alternatives using a copy of weighted preference lists including only the alternatives in said list of spoilers;

(b) removing the spoilers out of said replica of weighted preference lists by performing one or more methods selected from the group consisting of but not limited to;

(i.) removing at least one of spoilers in the list of spoilers out of said replica of weighted preference lists,

(ii.) removing the lowest ranked alternative in said sorted list of spoilers out of said replica of weighted preference lists,

(iii.) removing the alternatives of a combination that one of the members of the combination is the lowest ranked alternative in said sorted list of spoilers out of said replica of weighted preference lists, and

(iv.) removing a plurality of spoilers in said sorted list of spoilers out of said replica of weighted preference lists.

19. The method in claim 1, wherein each weighted preference list comprises:

(a) a ranked list of a set of alternatives comprising at least one of, but not limited to, the following;

(i.) a grouping of identical preferences of a plurality of evaluators about a set of sorted or scored alternatives wherein the number of alternatives in a list may be equal or different from other lists and said evaluators can be a plurality of humans, non-human means of evaluation, and mix of humans with non-humans,

(ii.) a ranking of preferences by an evaluator about a set of sorted or scored alternatives wherein the number of alternatives in a list may be equal or different from other lists and said evaluators comprises a plurality of;

humans, non-human means of evaluation, and mix of humans with non-humans;

(b) a weight which is a number assigned to said weighted preference list wherein said number is the presentation of at least one of, but not limited to, the following;

(i.) count, vote count, frequency, relative frequency of evaluators having same said preference,

(ii.) power, privilege, trust, significance, confidence, reliability, expertise of evaluators with same said preference,

(iii.) result of combining the count, vote count, frequency, relative frequency and the power, privilege, trust, significance, confidence, reliability, expertise of evaluators with same preference.

20. The method in claim 1, wherein an alternative is one of, but is not limited to, the following:

a value, a candidate or person, an opinion, a prediction, an attribute, an option, a behavior, a category, an advertisement, an entertainment selection, a document, place, a product, a thing or information, an action to be performed, a set of values, a range of numeric values, a group of attributes, a classification of objects, a category, a set of measurements, a future behaviors, a set of future behaviors, a set of options, a set of predictions, a set of candidates, a set of products, a set of objects, a set of solutions for problems, a set of observations, a set of controllable parameters, and a set of data collected from a group of sensors or their combinations.

21. The method of claim 1, used in selecting a collective choice set with proportional representation from alternatives in a set of weighted preference lists comprising the steps of:

(a) creating a temporary copy of said weighted preference lists;

(b) forming a top choice set consisting of the top choice of each temporary weighted preference list;

(c) assigning a significance number to each alternative in said top choice set by adding the weight number of those temporary weighted preference lists that have said alternative at the top;

(d) if said highest significance number is less than a predetermined quota, further comprising the steps of;

(i.) concluding this process if sum of the weights of alternatives remaining in said temporary weighted preference lists is less than said quota;

(ii.) finding lowest ranked alternatives by performing one of the following steps, selected from the group consisting of but not limited to;

I. employing said steps of claim 1 to produce an independent collective choice ordered list using a copy of said temporary weighted preference lists;

II. making a ranked list of alternatives by applying a collective choice procedure using a copy of said temporary weighted preference lists;

III. employing said steps of claim 1 to produce an independent collective choice ordered list using a copy of said temporary weighted preference lists including only the alternatives in said top choice set;

IV. making a ranked list of alternatives by applying a collective choice procedure using a copy of said temporary weighted preference lists including only the alternatives in said top choice set;

(iii.) removing at least one of the lowest ranked alternatives;

(iv.) repeating steps (b) to (d);

(e) if said highest significance number is greater than or equal to a predetermined quota and there is a unique highest ranked alternative, adding chosen alternative to the proportional collective choice set;

(f) if said highest significance number is greater than or equal to a predetermined quota and a plurality of alternatives have said equal significance, further comprising the steps of;

(i.) choosing among alternatives with significance greater than or equal to quota;

(ii.) adding chosen alternatives to intended proportional collective choice set;

(g) concluding this process if at least one of, but not limited to, the following happens;

sum of the weights of remaining alternatives in said temporary copy of

weighted preference lists is less than said quota,

a predetermined number of alternatives are added to the proportional

collective choice set,

a deadline has reached,

a decision is made,

a task is accomplished;

(h) reducing the weights of said weighted preference lists;

(i) removing said chosen alternatives from the weighted preference lists;

(j) repeating steps (a) to (j).

22. The method in claim 21, wherein choosing among alternatives with significance greater than or equal to quota comprises one of, but not limited to, the following:

(a) choosing a plurality of alternatives with significance number greater than or equal to said predetermined quota,

(b) selecting an independent collective choice employing said steps of claim 1 using said temporary weighted preference lists of only “

the alternatives with significance number greater than or equal to said predetermined quota”

,

(c) choosing the lowest ranked alternative in an independent collective choice ordered list produced by employing said steps of claim 1 using said temporary weighted preference lists of only “

the alternatives with significance number greater than or equal to said predetermined quota”

.

23. The method in claim 21, wherein reducing the weights of said weighted preference lists comprises one of, but not limited to, the following:

(a) proportionally subtracting said quota from the weight currently assigned to weighted preference lists contributing to the significance of each one of said chosen alternatives,

(b) subtracting said quota from the weight currently assigned to weighted preference lists with highest weight contributing to the significance of each one of said chosen alternatives equally as much as they have weight, and then similarly subtracting the remainder of quota from the weight of the next highest weight contributing lists,

(c) subtracting said quota from the weight currently assigned to weighted preference lists with lowest weight contributing to the significance of each one of said chosen alternatives equally as much as they have weight, and then similarly subtracting the remainder of quota from the weight of the next lowest weight contributing lists.

24. The method in claim 3, wherein ties in selecting the highest ranked alternative and selecting the lowest ranked alternative, are resolved using one or more methods selected from the group consisting of but not limited to:

(a) using a pair wise comparison if the tie is between two alternatives,

(b) using a method of making a ranked list of alternatives, with a collective choice procedure other than the one resulted the tie, to create a ranked list of tied alternatives using weighted preference lists that resulted the tie with only the alternatives in tie just to resolve the tie,

(c) using a method of making a ranked list of alternatives, with a collective choice procedure other than the one resulted the tie, to create a ranked list of alternatives that tied using weighted preference lists that resulted the tie,

(d) randomly selecting one of the tied alternatives,

(e) selecting a plurality of the tied alternatives.

25. A method for selecting a collective choice set with proportional representation from alternatives in a set of weighted preference lists comprising the steps of:

(a) creating a temporary copy of said weighted preference lists;

(b) forming a top choice set consisting of the top choice of each temporary weighted preference list;

(c) assigning a significance number to each alternative in said top choice set by adding the weight number of those temporary weighted preference lists that have said alternative at the top;

(d) if said highest significance number is less than a predetermined quota, further comprising the steps of;

(i.) concluding this process if sum of the weights of alternatives remaining in said temporary weighted preference lists is less than said quota;

(ii.) finding lowest ranked alternatives by performing one of the following steps, selected from the group consisting of but not limited to;

I. producing an independent collective choice ordered list using a copy of said temporary weighted preference lists;

II. making a ranked list of alternatives by applying a collective choice procedure using a copy of said temporary weighted preference lists;

III. producing an independent collective choice ordered list using a copy of said temporary weighted preference lists including only the alternatives in said top choice set;

IV. making a ranked list of alternatives by applying a collective choice procedure using a copy of said temporary weighted preference lists including only the alternatives in said top choice set;

(iii.) removing at least one of the lowest ranked alternatives;

(iv.) repeating steps (b) to (d);

(e) if said highest significance number is greater than or equal to a predetermined quota and there is a unique highest ranked alternative, adding chosen alternative to the proportional collective choice set;

(f) if said highest significance number is greater than or equal to a predetermined quota and a plurality of alternatives have said equal significance, further comprising the steps of;

(i.) choosing among alternatives with significance greater than or equal to quota;

(ii.) adding chosen alternatives to intended proportional collective choice set;

(g) concluding this process if at least one of, but not limited to, the following happens;

sum of the weights of remaining alternatives in said temporary copy of

weighted preference lists is less than said quota,

a predetermined number of alternatives are added to the proportional collective choice set,

a deadline has reached,

a decision is made,

a task is accomplished;

(h) reducing the weights of said weighted preference lists;

(i) removing said chosen alternatives from the weighted preference lists;

(j) repeating steps (a) to (j).

26. The method in claim 25, wherein choosing among alternatives with significance greater than or equal to quota comprises one of, but not limited to, the following:

(d) choosing a plurality of alternatives with significance number greater than or equal to said predetermined quota,

(e) selecting an independent collective choice using said temporary weighted preference lists of only “

the alternatives with significance number greater than or equal to said predetermined quota”

,

(f) producing an independent collective choice ordered list using said temporary weighted preference lists of only “

the alternatives with significance number greater than or equal to said predetermined quota”

choosing the lowest ranked alternative is said independent collective choice ordered list.

27. The method in claim 25, wherein reducing the weights of said weighted preference lists comprises one of, but not limited to, the following:

(d) proportionally subtracting said quota from the weight currently assigned to weighted preference lists contributing to the significance of each one of said chosen alternatives,

(e) subtracting said quota from the weight currently assigned to weighted preference lists with highest weight contributing to the significance of each one of said chosen alternatives equally as much as they have weight, and then similarly subtracting the remainder of quota from the weight of the next highest weight contributing lists,

(f) subtracting said quota from the weight currently assigned to weighted preference lists with lowest weight contributing to the significance of each one of said chosen alternatives equally as much as they have weight, and then similarly subtracting the remainder of quota from the weight of the next lowest weight contributing lists.

28. The method in claim 25, wherein selecting an independent collective choice and producing a independent collective choice ordered list using a given set of weighted preference lists, comprise the steps of:

(a) finding a preferred collective choice using given weighted preference lists while restricting the impact of spoilers and considering said choice as an independent collective choice;

(b) if an ordered list of independent collective choices should be produced, adding said independent collective choice as the next choice to the desired independent collective choice ordered list for given weighted preference lists, otherwise, concluding the decision process with said independent collective choice as decision outcome;

(c) if more alternatives should be selected performing the following steps;

(i.) deleting said independent collective choice from said given weighted preference lists;

repeating steps (a) to (c) until all the alternatives have been deleted from said given weighted preference lists.

29. The method in claim 28, further comprising the following step at the beginning of the process before step (a):

if the weight of one of the lists in given weighted preference lists, is greater than half of the total sum of weights of said given weighted preference lists, considering said list as the independent collective choice ordered list and its top choice as the independent collective choice and concluding the process, otherwise, continuing with step (a).

30. The method in claim 28, wherein finding a preferred collective choice using given weighted preference lists while restricting the impact of spoilers comprises the steps of:

(a) finding a highest ranked alternative, called strong alternative, using a copy of said given weighted preference lists excluding the spoilers signed in this process;

(b) creating a new list of spoilers using said given weighted preference lists excluding the spoilers signed in this process;

(c) if no spoilers are in the list of spoilers performing the following steps;

(i.) clearing the signs added in this process to said given weighted preference lists;

(ii.) concluding this process with the desired preferred collective choice being the last strong alternative just found in step (a);

(d) if any spoiler is in said list of spoilers, signing at least one spoiler out of said given weighted preference lists;

(e) repeating steps (a) to (e).

31. The method in claim 30, wherein creating a new list of spoilers comprises the steps of:

(a) setting a level-indicator to 1;

(b) concluding the creation of said list of spoilers if at least one of, but not limited to, the following happens;

(i.) the level-indicator is greater than “

the number of alternatives in given weighted preference lists, that are not signed”

minus 2,

(ii.) the level indicator is more than a predetermined level,

(iii.) a deadline has reached;

(c) selecting a new combination of alternatives, from alternatives in “

given weighted preference lists excluding;

the signed alternatives, said strong alternative, spoilers and spoiler combinations in list of spoilers”

, wherein the number of alternatives in the combination is the value of level-indicator;

(d) finding the highest ranked alternative using a copy of said given weighted preference lists without said selected combination of alternatives and without signed alternatives, by applying the same technique used in finding said strong alternative;

(e) if the highest ranked alternative found in step (d) is different than said strong alternative, adding said combination to the anticipated list of spoilers;

(f) If all valid combinations of alternatives at said level-indicator have not been tested, repeating the steps (c) to (f);

(g) incrementing said level-indicator by one;

(h) repeating steps (b) to (h).

32. The method in claim 30, wherein signing at least one spoiler out of said given weighted preference lists comprises the steps of:

(a) creating a sorted list of spoilers by applying one of methods selected from the group consisting of but not limited to;

(i.) recursively employing said steps of claim 28 to produce an independent collective choice ordered list using a copy of said given weighted preference lists including only the alternatives in said list of spoilers, and

(ii.) making a ranked list of alternatives using a copy of said given weighted preference lists including only the alternatives in said list of spoilers;

(b) signing the spoilers out of said given weighted preference lists by performing one or more methods selected from the group consisting of but not limited to;

(i.) signing at least one of spoilers in the list of spoilers out of said given weighted preference lists,

(ii.) signing the lowest ranked alternative in said sorted list of spoilers out of said given weighted preference lists,

(iii.) signing the alternatives of a combination that one of the members of the combination is the lowest ranked alternative in said sorted list of spoilers out of said given weighted preference lists, and

(iv.) signing a plurality of spoilers in said sorted list of spoilers out of said given weighted preference lists.

33. The method in claim 28, wherein finding a preferred collective choice using given weighted preference lists while restricting the impact of spoilers comprises the steps of:

(a) creating a replica of given weighted preference lists;

(b) finding a highest ranked alternative, called strong alternative, using a copy of said replica of weighted preference lists;

(c) creating a new list of spoilers using said replica of weighted preference lists;

(d) if no spoilers are in the list of spoilers concluding this process with the desired preferred collective choice being the last strong alternative just found in step (b);

(e) if any spoiler is in said list of spoilers, removing at least one spoiler out of said replica of weighted preference lists;

(f) repeating steps (b) to (f);

34. The method in claim 33, wherein creating a new list of spoilers comprises the steps of:

(a) setting a level-indicator to 1;

(b) concluding the creation of said list of spoilers if at least one of, but not limited to, the following happens;

(i.) the level-indicator is greater than “

the number of alternatives in supplied weighted preference lists”

minus 2,

(ii.) the level indicator is more than a predetermined level,

(iii.) a deadline has reached;

(c) selecting a new combination of alternatives, from alternatives in “

supplied weighted preference lists excluding said strong alternative, spoilers and spoiler combinations in list of spoilers”

, wherein the number of alternatives in the combination is the value of level-indicator;

(d) finding the highest ranked alternative using a copy of said supplied weighted preference lists without said selected combination of alternatives, by applying the same technique used in finding said strong alternative;

(e) if the highest ranked alternative found in step (d) is different than said strong alternative, adding said combination to the anticipated list of spoilers;

(f) If all valid combinations of alternatives at said level-indicator have not been tested, repeating the steps (c) to (f);

(g) incrementing said level-indicator by one;

(h) repeating steps (b) to (h).

35. The method in claim 33, wherein removing at least one spoiler out of said replica of weighted preference lists comprises the steps of:

(a) creating a sorted list of spoilers by applying one of methods selected from the group consisting of but not limited to;

(i.) recursively employing said steps of claim 28 to produce an independent collective choice ordered list using a copy of said weighted preference lists including only the alternatives in said list of spoilers, and

(ii.) making a ranked list of alternatives using a copy of weighted preference lists including only the alternatives in said list of spoilers;

(b) removing the spoilers out of said replica of weighted preference lists by performing one or more methods selected from the group consisting of but not limited to;

(i.) removing at least one of spoilers in the list of spoilers out of said replica of weighted preference lists,

(ii.) removing the lowest ranked alternative in said sorted list of spoilers out of said replica of weighted preference lists,

(iii.) removing the alternatives of a combination that one of the members of the combination is the lowest ranked alternative in said sorted list of spoilers out of said replica of weighted preference lists, and

(iv.) removing a plurality of spoilers in said sorted list of spoilers out of said replica of weighted preference lists.

36. The method in claim 25, wherein finding a highest ranked alternative and making a ranked list of alternatives using provided copy of weighted preference lists comprise applying one or more methods selected from the group consisting of but not limited to:

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method.

37. The method in claim 25, wherein finding a highest ranked alternative using a provided copy of weighted preference lists comprises the steps of:

(a) finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure;

(b) erasing said remaining alternative from said provided weighted preference lists;

(c) repeating steps (a) to (c) until said provided copy of weighted preference lists has no alternatives.

(d) Considering the last alternative erased as the highest ranked alternative.

38. The method in claim 37, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) finding the highest ranked alternative in said operational copy of weighted preference lists by applying a collective choice procedure selected from the group consisting of but not limited to;

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method;

(ii.) removing said highest ranked alternative from said operational copy of weighted preference lists;

39. The method in claim 37, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) selecting the first choice of each preference list in said operational copy of weighted preference lists;

(ii.) for each first choice selected, summing the weight of said weighted preference lists that have said first choice;

(iii.) selecting the alternative with the highest aggregated weight among said first choices;

(iv.) removing said highest ranked alternative from said operational copy of weighted preference lists.

40. The method in claim 37, further comprising a step to make a ranked list of alternatives performing the following after step (a):

adding said remaining alternative, as the highest ranked alternative so far, to the intended ranked list of alternatives.

41. The method in claim 25, wherein each weighted preference list comprises:

(a) a ranked list of a set of alternatives comprising at least one of, but not limited to, the following;

(i.) a grouping of identical preferences of a plurality of evaluators about a set of sorted or scored alternatives wherein the number of alternatives in a list may be equal or different from other lists and said evaluators can be a plurality of humans, non-human means of evaluation, and mix of humans with non-humans,

(ii.) a ranking of preferences by an evaluator about a set of sorted or scored alternatives wherein the number of alternatives in a list may be equal or different from other lists and said evaluators comprises a plurality of;

humans, non-human means of evaluation, and mix of humans with non-humans;

(b) a weight which is a number assigned to said weighted preference list wherein said number is the presentation of at least one of, but not limited to, the following;

(i.) count, vote count, frequency, relative frequency of evaluators having same said preference,

(ii.) power, privilege, trust, significance, confidence, reliability, expertise of evaluators with same said preference,

(iii.) result of combining the count, vote count, frequency, relative frequency and the power, privilege, trust, significance, confidence, reliability, expertise of evaluators with same preference.

42. The method in claim 25, wherein an alternative is one of, but is not limited to, the following:

a value, a candidate or person, an opinion, a prediction, an attribute, an option, a behavior, a category, an advertisement, an entertainment selection, a document, place, a product, a thing or information, an action to be performed, a set of values, a range of numeric values, a group of attributes, a classification of objects, a category, a set of measurements, a future behaviors, a set of future behaviors, a set of options, a set of predictions, a set of candidates, a set of products, a set of objects, a set of solutions for problems, a set of observations, a set of controllable parameters, and a set of data collected from a group of sensors or their combinations.

43. A method for finding the highest ranked alternative using a provided set of weighted preference lists by repeatedly choosing the highest ranking alternative comprising the steps of:

(a) finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure;

(b) erasing said remaining ranked alternative from said provided weighted preference lists;

(c) If a collective choice set should be selected and said provided copy of weighted preference lists has a predetermined number of alternatives, considering them as the collective choice set;

(d) repeating steps (a) to (e) until said provided copy of weighted preference lists has no remaining alternatives;

(e) Considering the last alternative erased as the highest ranked alternative.

44. The method in claim 43, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) finding the highest ranked alternative in said operational copy of weighted preference lists by applying a collective choice procedure selected from the group consisting of but not limited to;

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method;

(ii.) removing said highest ranked alternative from said operational copy of weighted preference lists;

45. The method in claim 43, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) repeating the following steps until there is only one alternative in said operational copy of weighted preference lists;

(i.) finding the highest ranked alternative in said operational copy of weighted preference lists by applying a collective choice procedure selected from the group consisting of but not limited to;

a Nanson'"'"'s method, a Baldwin method, a Ranked Pairs method, a Coombs'"'"' method, a Schulze method, a Kemeny-Young method, a Condorcet scoring method, a Borda Count method, a Copeland'"'"'s method, a rating summation method, and a plurality method;

(ii.) temporarily removing said highest ranked alternative from said operational copy of weighted preference lists;

(b) considering the one remaining alternative as the outcome;

(c) re-including all the temporarily removed alternatives in said weighted preference lists;

46. The method in claim 43, wherein finding a remaining alternative by repeatedly removing the highest ranked alternative by applying a collective choice procedure comprises:

(a) making an operational copy of provided weighted preference lists;

(b) repeating the following steps until there is only one alternative, remaining alternative, in said operational copy of weighted preference lists;

(i.) selecting the first choice of each preference list in said operational copy of weighted preference lists;

(ii.) for each first choice selected, summing the weight of said weighted preference lists that have said first choice;

(iii.) selecting the alternative with the highest aggregated weight among said first choices;

(iv.) removing said highest ranked alternative from said operational copy of weighted preference lists.

47. The method in claim 43, further comprising a step to make a ranked list of alternatives comprising the following step after step (b):

adding said remaining alternative, as the highest ranked alternative so far, to the intended ranked list of alternatives.

48. A method for, finding spoilers in a set weighted preference lists comprising the steps of:

(a) finding a highest ranked alternative called strong alternative using said weighted preference lists;

(b) setting a level-indicator to 1;

(c) concluding the creation of said list of spoilers if at least one of, but not limited to, the following happens;

(i.) the level-indicator is greater than “

the number of alternatives in weighted preference lists”

minus 2,

(ii.) the level indicator is more than a predetermined level,

(iii.) a deadline has reached;

(d) selecting a new combination of alternatives, from alternatives in “

said weighted preference lists excluding said strong alternative, spoilers and spoiler combinations in list of spoilers”

, wherein the number of alternatives in the combination is the value of level-indicator;

(e) finding the highest ranked alternative using a copy of said given weighted preference lists without said selected combination of alternatives, by applying the same technique used in finding said strong alternative;

(f) if the highest ranked alternative found in step (e) is different than said strong alternative, adding said combination to the anticipated list of spoilers;

(g) If all valid combinations of alternatives at said level-indicator have not been tested, repeating the steps (d) to (g);

(h) incrementing said level-indicator by one;

(i) repeating steps (c) to (i).