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Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

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Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

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Today, the editor brings you the article "Analysis of the Evolutionary Game of Agricultural Supply Chain Finance in the Context of Government Intervention".

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Dear, this is the LearingYard Academy!

Today, the editor brings the "Game Analysis of Agricultural Supply Chain Finance Evolution under Government Involvement Scenario".

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1 内容摘要(Content summary)

Today, the editor will interpret and share the Mathematica code part of the evolutionary game in Chapter 5 of the article "Analysis of the Evolutionary Game of Agricultural Supply Chain Finance in the Context of Government Intervention" from the three sections of "Mind Map, Intensive Reading Content, and Knowledge Supplement".

Today, I will read and share the Mathematica code part of the evolutionary game in the fifth chapter of the article "Analysis of Agricultural Supply Chain Finance Evolutionary Game under the Scenario of Government Intervention" in the three sections of "Thinking Maps, Intensive Reading, and Knowledge Supplementation".

2 思维导图(Mind mapping)

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

3 精读内容(Intensive reading content)

3.1 Evolutionary Game Computation in Context A

3.1 Evolutionary game computation in context A

Continuing from the previous section, calculate the value and rank of the determinant at different values of x and y:

Picking up from the previous section, compute the value and rank of the determinant for different values of x,y:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)
Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)
Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)
Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

3.2 Evolutionary game computation in scenario B (government intervention).

3.2 Calculation of the evolutionary game in scenario B (government intervention)

  1. 1. Calculate the expected return and its comprehensive expected return under different decisions of leading agricultural enterprises and the replication dynamic equation of leading agricultural enterprises:

1. calculate the expected returns under different decisions of leading agricultural enterprises and their combined expected returns and the replication dynamic equation for leading agricultural firms:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

2. Calculate the expected return and its comprehensive expected return under different decisions of farmers and the replication dynamic equation of farmers:

2. Calculate the expected returns of smallholders under different decisions and their combined expected returns and the replication dynamic equation :

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

3. Find the partial derivatives of the replication dynamic equations F1 and F2 respectively:

3. find the partial derivatives for the replicated dynamic equations F1 and F2, respectively:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

4. Solve the replication dynamic equations F1 and F2 respectively:

4. solve the replicated dynamic equations F1 and F2 separately:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

5. Construct a Jacobian matrix and analyze the equilibrium points of the game:

5. Construct the Jacobi matrix and perform game equilibrium point analysis:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

6. Extract each element for simplification:

6. Extract the elements for simplification:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

7. Calculate the value and rank of the determinant under different values of x,y:

7.Calculate the value and rank of the determinant for different values of x,y:

Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)
Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)
Whispering (51): Intensive Reading of Master's and Doctoral Theses-B Scenario Simulation-Mathematica Computation (2)

4 知识补充(Knowledge supplement)

政府介入可以对演化博弈中的哪些变量起到影响?( What variables in the evolutionary game can be influenced by government intervention?)

1. Rulemaking: Governments can regulate the behavior of participants in games by enacting laws, regulations, or policies. These rules can influence strategy choices and outcomes in evolutionary games.

  1. 1. Rule-making: Governments can regulate the behavior of participants in the game by enacting laws, regulations or policies. These rules can influence strategy choices and outcomes in evolutionary games
  2. 2. Rewards and punishments: Governments can incentivize or constrain participants' behavior by offering rewards or imposing punishments. This may include tax policies, subsidy programs, fines, or regulatory measures.
  3. 2. Incentives and penalties: Governments can incentivize or constrain participant behavior by providing incentives or imposing penalties. This may include tax policies, subsidy programs, fines or regulatory measures.
  4. 3. Resource allocation: The government can influence the choice of strategy in the evolutionary game through resource allocation. For example, governments can change the environmental conditions of their participants by investing in infrastructure or providing public services.
  5. 3. Resource allocation: Governments can influence strategic choices in evolutionary games through resource allocation. For example, governments can change the environmental conditions of participants by investing in infrastructure or providing public services.

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Reference: ChatGPT

Bibliography:

WANG Jingjing. Evolutionary game analysis of agricultural supply chain finance under the context of government intervention [D]. Yunnan: Yunnan Normal University, 2022.

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