Payoff matrix creation and real-time decision analysis with multiple decision criteria support. Including Maximax, Maximin, Laplace, Savage, Hurwicz, Action Expected Value (VEA), Perfect Information Expected Value (VEIP) and optimal alternative.
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Maximax: a criterion for risk-takers, it selects the alternative with the maximum possible payoff, focusing on the most optimistic scenario.
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Maximin: a conservative criterion that chooses the alternative with the best worst-case outcome, prioritizing risk minimization.
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Laplace: assumes all outcomes are equally likely and selects the alternative with the highest average payoff, balancing optimism and pessimism.
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Savage: also known as the minimax, it chooses the alternative that minimizes the maximum regret, focusing on avoiding missed opportunities.
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Hurwicz: a compromise between optimism and pessimism, this criterion weights the best and worst payoffs with a coefficient to find a balance in decision-making.
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Action Expected Value (VEA): calculates the expected payoff for each alternative, taking into account probabilities, to select the best choice.
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Perfect Information Expected Value (VEIP): measures the value of knowing the outcome with certainty before making a decision, comparing the expected benefit of perfect information with the best action under uncertainty.
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Optimal Alternative: The decision that provides the best overall outcome based on all decision criterion.
See the project in action here.
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Clone the repository.
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Make sure you have Flutter 3.24.2 installed.
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Navigate to the project directory and install dependencies:
cd payoff_matrix
flutter pub get- Run the app:
flutter runThis project is licensed under the BSD (3-Clause) License - see the LICENSE file for details.