[74] | 1 | from geniusweb.issuevalue.Value import Value
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| 2 | from geniusweb.issuevalue.Bid import Bid
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| 3 | from geniusweb.issuevalue.Domain import Domain
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| 4 |
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| 5 | class FrequencyAnalyzer:
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| 6 | def __init__(self) -> None:
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| 7 | self.number_bids: int = 0
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| 8 | self.last_bid = None
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| 9 | self.domain: Domain
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| 10 |
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| 11 | self.frequency_table: dict[str, tuple[float, dict[Value, float], int]] = {}
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| 12 |
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| 13 | def set_domain(self, domain: Domain):
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| 14 | self.domain = domain
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| 15 |
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| 16 | def _init_table(self) -> None:
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| 17 | if self.last_bid is None:
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| 18 | raise MissingHistoryException()
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| 19 |
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| 20 | issues = self.domain.getIssues()
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| 21 |
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| 22 | # init frequency table
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| 23 | for issue in issues:
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| 24 | values = self.domain.getValues(issue)
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| 25 | value_freqs = { value : 0.0 for value in values }
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| 26 | self.frequency_table[issue] = (1.0/float(len(issues)), value_freqs, 0)
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| 27 |
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| 28 | issues_in_bid = self.last_bid.getIssues()
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| 29 |
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| 30 | # init with first bid
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| 31 | for issue in issues_in_bid:
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| 32 | freq, value_freqs, value_max_occurence = self.frequency_table[issue]
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| 33 |
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| 34 | freq: float = 1/len(issues_in_bid)
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| 35 | issue_value = self.last_bid.getValue(issue)
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| 36 |
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| 37 | if issue_value is None:
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| 38 | raise ValueIsNoneException()
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| 39 |
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| 40 | value_freqs[issue_value] = 1.0
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| 41 | value_max_occurence: int = 1
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| 42 |
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| 43 | self.frequency_table[issue] = (freq, value_freqs, value_max_occurence)
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| 44 |
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| 45 |
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| 46 | def _update_issue_frequency(self, bid: Bid, issue: str, n) -> None:
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| 47 | if self.last_bid is None:
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| 48 | raise MissingHistoryException()
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| 49 |
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| 50 | issues = self.domain.getIssues()
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| 51 |
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| 52 | # if an issue has the same value
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| 53 | if self.last_bid.getValue(issue) == bid.getValue(issue):
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| 54 | # update frequency of current bid
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| 55 | freq, value_freqs, value_max_occurence = self.frequency_table[issue]
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| 56 | self.frequency_table[issue] = ((freq * self.number_bids + 1)/float(self.number_bids + 1), value_freqs, value_max_occurence)
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| 57 |
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| 58 | for other_issue in issues:
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| 59 | # and 'compensate' this frequency change with others
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| 60 | if issue != other_issue:
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| 61 | other_freq, other_value_freqs, other_value_max_occurence = self.frequency_table[other_issue]
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| 62 | self.frequency_table[other_issue] = ((other_freq * self.number_bids)/float(self.number_bids + 1), other_value_freqs, other_value_max_occurence)
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| 63 |
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| 64 | def _update_issue_value_frequency(self, current_value, issue: str) -> None:
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| 65 | if current_value is None:
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| 66 | raise ValueIsNoneException()
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| 67 |
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| 68 | freq, value_freqs, value_max_occurence = self.frequency_table[issue]
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| 69 | current_freq = value_freqs[current_value]
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| 70 |
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| 71 | if current_freq == 1.0:
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| 72 | max_repeat = 1
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| 73 | else:
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| 74 | max_repeat = 0
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| 75 |
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| 76 | for value in self.domain.getIssuesValues()[issue]:
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| 77 | if value == current_value:
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| 78 | occurence = 1
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| 79 | else:
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| 80 | occurence = 0
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| 81 |
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| 82 | value_freqs[value] = ((value_freqs[value] * value_max_occurence) + occurence) / (value_max_occurence + max_repeat)
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| 83 |
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| 84 | self.frequency_table[issue] = (freq, value_freqs, value_max_occurence + max_repeat)
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| 85 |
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| 86 | def add_bid(self, bid: Bid, n: float =.1) -> None:
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| 87 | if bid is None:
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| 88 | return
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| 89 |
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| 90 | if self.last_bid is None:
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| 91 | self.last_bid = bid
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| 92 | self._init_table()
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| 93 | return
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| 94 |
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| 95 | for issue in self.domain.getIssues():
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| 96 | self._update_issue_frequency(bid, issue, n)
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| 97 | self._update_issue_value_frequency(bid.getValue(issue), issue)
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| 98 |
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| 99 | self.number_bids += 1
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| 100 |
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| 101 | def _get_max_value(self, issue: str) -> Value:
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| 102 | _, value_frequencies, _ = self.frequency_table[issue]
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| 103 | max_freq: float = -1.0
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| 104 | max_key = None
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| 105 |
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| 106 | for key, freq in value_frequencies.items():
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| 107 | if max_freq < freq:
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| 108 | max_freq = freq
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| 109 | max_key = key
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| 110 |
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| 111 | assert max_key is not None
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| 112 |
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| 113 | return max_key
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| 114 |
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| 115 | """
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| 116 | Returns an approximation of the opponents utility for the given bid
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| 117 | """
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| 118 | def get_utility(self, bid: Bid):
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| 119 | utility = 0.0
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| 120 |
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| 121 | for issue in self.domain.getIssues():
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| 122 | freq, value_freqs, _ = self.frequency_table[issue]
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| 123 | issue_value = bid.getValue(issue)
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| 124 | if issue_value is not None:
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| 125 | # Take the 'importance' of the current issue, and multiply it by the utility with the associated value
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| 126 | utility += freq * value_freqs[issue_value]
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| 127 | # sum of all importances is 1.0
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| 128 | # best values of each issue is always 1.0
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| 129 | # => max utility is 1.0, thus admissable
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| 130 | else:
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| 131 | utility += 0
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| 132 |
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| 133 | return utility
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| 134 |
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| 135 | """
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| 136 | Return a list of issues and the difference in their importance [0.0, 1.0]
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| 137 | The higher the number, the better the compatibility
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| 138 | """
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| 139 | def utility_compatibility(self, other_importance: dict[str, float]) -> dict[str, float]:
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| 140 | compatibility: dict[str, float] = dict()
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| 141 |
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| 142 | for issue in self.domain.getIssues():
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| 143 | freq, _, _ = self.frequency_table[issue]
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| 144 | compatibility[issue] = abs(other_importance[issue] - freq)
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| 145 |
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| 146 | return compatibility
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| 147 |
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| 148 | """
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| 149 | Return next predicted bid based on frequency analysis
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| 150 | """
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| 151 | def predict(self) -> Bid:
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| 152 | if len(self.frequency_table) == 0:
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| 153 | raise MissingHistoryException()
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| 154 |
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| 155 | prediction: dict[str, Value] = {}
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| 156 |
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| 157 | for issue in self.frequency_table:
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| 158 | prediction[issue] = self._get_max_value(issue)
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| 159 |
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| 160 | return Bid(prediction)
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| 161 |
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| 162 |
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| 163 | class MissingHistoryException(Exception):
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| 164 | def __init__(self, *args: object) -> None:
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| 165 | super().__init__(*args)
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| 166 |
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| 167 | class ValueIsNoneException(Exception):
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| 168 | def __init__(self, *args: object) -> None:
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| 169 | super().__init__(*args)
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| 170 |
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| 171 | class BidIsNoneException(Exception):
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| 172 | def __init__(self, *args: object) -> None:
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| 173 | super().__init__(*args)
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