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Cooperative Dynamic Games with Durable Controls: Theory and Application

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Abstract

Durable controls that have effects lasting over a certain period of time are prevalent in real-life situations. Revenue-generating investments, toxic waste disposal, durable goods, emission of pollutants, regulatory measures, coalition agreements, diffusion of knowledge, advertisement and investments to build up physical capital are vivid examples of durable controls. Durable controls may affect both the decision-makers’ payoffs and the evolution of the state dynamics. This paper develops a new class of cooperative dynamic games with multiple durable controls of different lag durations affecting both the players’ payoffs and the state dynamics. A novel dynamic optimization theorem involving durable controls is derived. Dynamically consistent cooperative solutions are provided. An illustration of a dynamic game with durable controls causing lagged effects in capital formation, pollution accumulation and revenue generation from investment is presented. The analysis widens the application of dynamic game theory in practical problems. Further theoretical developments and relevant applications along this line would be expected.

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References

  1. Agliardi E, Koussisc N (2013) Optimal capital structure and the impact of time-to-build. Financ Res Lett 10:124–130

    Article  Google Scholar 

  2. Arthur WB (1977) Control of linear processes with distributed lags using dynamic programming from first principles. J Optim Theory Appl 23:429–443

    Article  MathSciNet  Google Scholar 

  3. Basar T (2018) Zaccour G (2018) Handbook of dynamic game theory, volume 1 and volume 2. Springer, Berlin

    Book  Google Scholar 

  4. Bellman R (1957) Terminal control, time lags, and dynamic programming. Proc Natl Acad Sci USA 43:927–930

    Article  MathSciNet  Google Scholar 

  5. Bokov GV (2011) Pontryagin’s maximum principle of optimal control problems with time-delay. J Math Sci 172:623–634

    Article  MathSciNet  Google Scholar 

  6. Brandt-Pollmann U, Winkler R, Sager S, Moslener U, Schlöder J (2008) Numerical solution of optimal control problems with constant control delays. Comput Econ 31:181–206

    Article  Google Scholar 

  7. Burdet CA, Sethi SP (1976) On the maximum principle for a class of discrete dynamical systems with lags. J Optim TheoryAppl 19:445–454

    Article  MathSciNet  Google Scholar 

  8. Christiano LJ, Eichenbaum M, Evans CL (2005) Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy. J Polit Econ 113:1–45

    Article  Google Scholar 

  9. Hartl RF, Sethi SP (1984) Optimal control of a class of systems with continuous lags: dynamic programming approach and economic interpretations. J OptimTheory Appl 43(1):73–88

    Article  MathSciNet  Google Scholar 

  10. Huschto T, Feichtinger G, Hartl RF, Kort PM, Sager S (2011) Numerical solution of a conspicuous consumption model with constant control delay. Automatica 47:1868–1877

    Article  MathSciNet  Google Scholar 

  11. Jørgensen S, Zaccour G (2004) Differential Games in Marketing. Kluwer Academic Publishers, The Netherlands

    Book  Google Scholar 

  12. Long NV (2010) A survey of dynamic games in economics. World Scientific, Singapore

    Book  Google Scholar 

  13. Mela CF, Gupta S, Lehmann DR (1997) The long-term impact of promotion and advertising on consumer brand choice. J Market Res 34:248–261

    Article  Google Scholar 

  14. Rood RB (2014) What would happen to the climate if we stopped emitting greenhouse gases today? The Conversation, December 11, 2014, https://www.iflscience.com/environment/what-would-happen-climate-if-we-stopped-emitting-greenhouse-gases-today/

  15. Rood RB (2017) If we stopped emitting greenhouse gases right now, would we stop climate change? The Conversation, July 5, 2017, theconversation.com/if-we-stopped-emitting-greenhouse-gases-right-now-would-we-stop-climate-change-78882

  16. Ruffino CC (2008) Lagged effects of TV advertising on sales of an intermittently advertised product. Business Econ Rev 18:1–12

    Google Scholar 

  17. Sarkar S, Zhang H (2013) Implementation lag and the investment decision. Econ Lett 119:136–140

    Article  MathSciNet  Google Scholar 

  18. Sarkar S, Zhang C (2015) Investment policy with time-to-build. J Bank Financ 55:142–156

    Article  Google Scholar 

  19. Sethi SP, Mcguire TW (1977) Optimal skill mix: an application of the maximum principle for systems with retarded controls. J Optim Theory and Appl 23:245–275

    Article  MathSciNet  Google Scholar 

  20. Shibata A, Shintani M, Tsurugac T (2019) Current account dynamics under information rigidity and imperfect capital mobility. J Int Money Financ 92:153–167

    Article  Google Scholar 

  21. Tellis GJ (2006) Optimal data interval for estimating advertising response. Market Sci 25:217–229

    Article  Google Scholar 

  22. Tsuruga T, Shota W (2019) Money-financed fiscal stimulus: the effects of implementation lag. Journal of Economic Dynamics and Control 104:132–151

    Article  MathSciNet  Google Scholar 

  23. Winkler R, Brandt-Pollmann U, Moslener U, Schlöder J (2003) Time-lags in capital accumulation. In: Ahr D, Fahrion R, Oswald M, Reinelt G (eds) Operations research proceedings. Springer, Berlin, pp 451–458

    Google Scholar 

  24. Wong KH, Clements DJ, Teo KL (1985) Optimal control computation for nonlinear time-lag systems. J Optim Theory Appl 47:91–107

    Article  MathSciNet  Google Scholar 

  25. Yeung DWK, Petrosyan LA (2010) Subgame consistent solutions for cooperative stochastic dynamic games. J Optim Theory Appl 145:579–596

    Article  MathSciNet  Google Scholar 

  26. Yeung DWK, Petrosyan LA (2016) Subgame consistent cooperation: a comprehensive treatise. Springer. https://doi.org/10.1007/978-981-10-1545-8

    Article  MATH  Google Scholar 

  27. Yeung DWK, Petrosyan LA (2019) Cooperative dynamic games with control lags. Dyn Games Appl 9:550–567

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors would like to thank two anonymous referees and the editor for their invaluable comments and suggestions. The research supports from the RSF (Russian Science Foundation) Grant N 17-11-01079 and the Longbow Foundation Grant are gratefully acknowledged.

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Correspondence to David W.K. Yeung.

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Appendices

Appendix A: Proof of Theorem 2.1

To prove Theorem 2.1, we adopt the technique of backward induction. Consider first the last operational stage \( T \); invoking Theorem 2.1, we have

$$ W(T,x;u_{T - } ) = \mathop {\hbox{max} }\limits_{{u_{T}^{{}} }} \left\{ {g_{T} \left( {x,u_{T} ;u_{T - } } \right) + q_{T + 1} \left[ {f_{T} (x,u_{T} ;u_{T - } );u_{(T + 1) - } } \right]} \right\}. $$
(A.1)

The maximization operator in stage \( T \) involves \( u_{T}^{{}} \) only. However, the current state \( x \) and the previously executed controls \( u_{T - }^{{}} \) appear in the stage \( T \) maximization problem as given parameters. If the first-order conditions of the maximization problem in (A.1) satisfy the implicit function theorem, one can obtain the optimal controls \( u_{T}^{{}} \) as functions of \( x \) and \( u_{T - }^{{}} \). Substituting these optimal controls into the function on the RHS of (A.1) yields the function \( W(T,x;u_{T - }^{{}} ) \), which satisfies the optimal conditions of a maximum for given \( x \) and \( u_{T - }^{{}} \).

Consider the second last operational stage \( T - 1 \); invoking Theorem 2.1, we have

$$ \begin{aligned} W\left( {T - 1,x;u_{(T - 1) - } } \right) & = \mathop {\hbox{max} }\limits_{{u_{T - 1} }} \left\{ {g_{T - 1} \left( {x,u_{T - 1} ;u_{(T - 1) - } } \right)} \right. \\ & \quad + \;\left. {W\left[ {T,f_{T - 1} \left( {x,u_{T - 1} ;u_{(T - 1) - } } \right);u_{T - } } \right]} \right\}. \\ \end{aligned} $$
(A.2)

The maximization operator in stage \( T - 1 \) involves \( u_{T - 1}^{{}} \). The current state \( x \) and the previously executed controls \( u_{(T - 1) - }^{{}} \) appear in the stage \( T - 1 \) maximization problem as given parameters. If the first-order conditions of the maximization problem in (A.2) satisfy the implicit function theorem, one can obtain the optimal controls \( u_{T - 1}^{{}} \) as functions of \( x \) and previously determined controls \( u_{(T - 1) - }^{{}} \). Substituting these optimal controls into the function on the RHS of (A.2) yields the function \( W(T - 1,x;u_{(T - 1) - }^{{}} ) \).

Now consider stage \( k \in \{ T - 2,T - 3, \cdots ,2,1\} \); invoking Theorem 2.1, we have

$$ W(k,x;u_{k - } ) = \mathop {\hbox{max} }\limits_{{u_{k} }} \left\{ {g_{k} (x,u_{k} ;u_{k - } ) + W\left[ {k + 1,f_{k} (x,u_{k} ;u_{k - } );u_{(k + 1) - } } \right]} \right\}. $$
(A.3)

The maximization operator involves \( u_{k}^{{}} \). Again, the current state \( x \) and the previously executed controls \( u_{k - }^{{}} \) appear in the stage \( k \) optimization problem. If the first-order conditions of the maximization problem in (A.3) satisfy the implicit function theorem, one can obtain the optimal controls \( u_{k}^{{}} \) as functions of \( x \) and \( u_{k - }^{{}} \). Substituting these optimal controls into the function on the RHS of (A.3) yields the function \( W(k,x;u_{k - }^{{}} ) \). □

Appendix B: Proof of Theorem 3.3

Using (3.12), one can obtain

$$ \begin{aligned} \xi^{i} \left( {k + 1,x_{k + 1}^{*} ;\underline{u}_{k - }^{*} } \right) & = B_{k + 1}^{i} \left( {x_{k + 1}^{*} ;\underline{u}_{k - }^{*} } \right) \\ & \quad + \;\left\{ {\sum\limits_{\zeta = k + 2}^{T} {B_{\zeta }^{i} \left( {x_{\zeta }^{*} ;\underline{u}_{\zeta - }^{*} } \right) + q_{T + 1}^{i} \left( {x_{T + 1} ;\underline{u}_{(T + 1) - }^{*} } \right)} } \right\}, \\ \end{aligned} $$
(B.1)

Upon substituting (B.1) into (3.12) yields

$$ \xi_{{}}^{i} (k,x_{k}^{*} ;\underline{u}_{k - }^{*} ) = B_{k}^{i} (x_{k}^{*} ;\underline{u}_{k - }^{*} ) + \xi_{{}}^{i} (k + 1,x_{k + 1}^{*} ;\underline{u}_{(k + 1) - }^{*} ), $$

which can be expressed as

$$ \xi^{i} \left( {k,x_{k}^{*} ;\underline{u}_{k - }^{*} } \right) = B_{k}^{i} \left( {x_{k}^{*} ;\underline{u}_{k - }^{*} } \right) + \xi^{i} \left( {k + 1,f_{k} \left( {x_{k}^{*} ,\underline{u}_{k}^{*} ;\underline{u}_{k - }^{*} } \right);\underline{u}_{(k + 1) - }^{*} } \right). $$
(B.2)

From (B.2), one can obtain Theorem 3.3. □

Appendix C: Proof of Proposition 4.1

From the terminal payoff in (4.5), we have

$$ \begin{aligned} & W\left( {T + 1,x,y;\underline{u}_{(T + 1) - }^{(2)} ,\underline{u}_{(T + 1) - }^{(3)} ,\underline{u}_{(T + 1) - }^{(4)} } \right) \\ & \quad = \sum\limits_{i = 1}^{n} {\left( {Q_{T + 1}^{(x)i} x_{T + 1} + Q_{T + 1}^{(y)i} y_{T + 1} + \sum\limits_{\tau = T - 1}^{T} {p_{T + 1}^{(\tau )i} u_{\tau }^{(3)i} } + \varpi_{T + 1}^{i} } \right)\delta^{T} } , \\ \end{aligned} $$

and therefore, we obtain

$$ A_{T + 1} = \sum\limits_{i = 1}^{n} {Q_{T + 1}^{(x)i} } ,{\kern 1pt} \quad B_{T + 1} = \sum\limits_{i = 1}^{n} {Q_{T + 1}^{(y)i} } ,\;{\text{and}}\;C_{T + 1} = \sum\limits_{i = 1}^{n} {\sum\limits_{\tau = T - 1}^{T} {\left( {p_{T + 1}^{(\tau )i} u_{\tau }^{(3)i} + \varpi_{T + 1}^{i} } \right)} } . $$
(C.1)

We begin with the last operating stage and consider the problem in stage \( T \)

$$ \begin{aligned} W\left( {T,x,y;\underline{u}_{T - }^{(2)} ,\underline{u}_{T - }^{(3)} ,\underline{u}_{T - }^{(4)} } \right) & = \mathop {\hbox{max} }\limits_{\substack{ u_{T}^{(1)i} ,u_{T}^{(2)i} ,\,u_{T}^{(3)i} ,u_{T}^{(4)i} \\ i \in N\; } } \left\{ {\sum\limits_{i = 1}^{n} {\left( {\alpha_{T}^{i} x - c_{T}^{i} \left( {u_{T}^{(2)i} } \right)^{2} } \right.} } \right. \\ & \quad - \;\gamma_{T}^{i} \left( {u_{T}^{(3)i} } \right)^{2} + \sum\limits_{\tau = T - 2}^{T} {p_{T}^{(\tau )i} u_{\tau }^{(3)i} } + \left[ {P_{T}^{i} u_{T}^{(4)i} - w_{T}^{i} (u_{T}^{(4)i} )^{2} } \right] - \left. {\varepsilon_{T}^{i} \left( {u_{T}^{(1)i} } \right)^{2} - h_{T}^{i} y} \right)\delta^{T - 1} \\ & \left. {\quad + \;\sum\limits_{i = 1}^{n} {\left( {Q_{T + 1}^{(x)i} x_{T + 1} + Q_{T + 1}^{(y)i} y_{T + 1} + \sum\limits_{\tau = T - 1}^{T} {p_{T + 1}^{(\tau )i} u_{\tau }^{(3)i} + \varpi_{T + 1}^{i} } } \right)} \delta^{T} } \right\}, \\ \end{aligned} $$
(C.2)

where \( x_{T + 1} = x + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 1}^{T} {a_{T}^{(\tau )j} u_{\tau }^{(2)j} } - \lambda \,x} , \)\( y_{T + 1} = y + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 3}^{T} {m_{T}^{(\tau )j} u_{\tau }^{(4)j} } } - \sum\limits_{j = 1}^{n} {b^{j} u_{T}^{(1)j} } (y)^{1/2} - \vartheta \,y \).Performing the indicated maximization in (C.2) yields the optimal cooperative strategies:

$$ \begin{aligned} u_{T}^{(1)i} & = - B_{T + 1} \frac{{b^{i} (y)^{1/2} \delta }}{{2\varepsilon_{T}^{i} }}, \\ u_{T}^{(2)i} & = \delta A_{T + 1} \frac{{a_{T}^{(T)i} }}{{2c_{T}^{i} }}, \\ u_{T}^{(3)i} & = \left( {p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} } \right)\frac{1}{{2\gamma_{T}^{i} }},\;{\text{and}} \\ u_{T}^{(4)i} & = \frac{{P_{T}^{i} + \delta B_{T + 1}^{{}} m_{T}^{(T)i} }}{{2w_{T}^{i} }},i \in N. \\ \end{aligned} $$
(C.3)

Invoking Proposition 4.1 and substituting (C.3) into the stage \( T \) equation in (C.2), we obtain:

$$ \begin{aligned} W\left( {T,x,y;\underline{u}_{T - }^{(2)} ,\underline{u}_{T - }^{(3)} ,\underline{u}_{T - }^{(4)} } \right) & = \left( {A_{T} x + B_{T} y + C_{T} } \right)\delta^{T - 1} \\ & = \sum\limits_{i = 1}^{n} {\left[ {\alpha_{T}^{i} x - c_{T}^{i} \left( {\frac{{\delta A_{T + 1}^{{}} a_{T}^{(T)i} }}{{2c_{T}^{i} }}\,} \right)^{2} - \gamma_{T}^{i} \left( {\frac{{p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} }}{{2\gamma_{T}^{i} }}} \right)^{2} } \right.} \\ & \quad + \;p_{T}^{(T)i} \left( {\frac{{p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} }}{{2\gamma_{T}^{i} }}} \right) + \sum\limits_{\tau = T - 2}^{T - 1} {p_{T}^{(\tau )i} u_{\tau }^{(3)i} } + P_{T}^{i} \left( {\frac{{P_{T}^{i} + \delta A_{T + 1} m_{T}^{(T)i} }}{{2w_{T}^{i} }}} \right) \\ & \left. {\quad - \;w_{T}^{i} \left( {\frac{{P_{T}^{i} + \delta A_{T + 1} m_{T}^{(T)i} }}{{2w_{T}^{i} }}} \right)^{2} - \varepsilon_{T}^{i} \left( {B_{T + 1} \frac{{b^{i} (y)^{1/2} \delta }}{{2\varepsilon_{T}^{i} }}} \right)^{2} - h_{T}^{i} y} \right]\delta^{T - 1} \\ & \quad + \;\left[ {A_{T + 1} \left( {x + \sum\limits_{j = 1}^{n} {a_{T}^{(T)j} \left( {\frac{{\delta A_{T + 1} a_{T}^{(T)j} }}{{2c_{T}^{j} }}} \right)} + \sum\limits_{j = 1}^{n} {a_{T}^{(T - 1)j} u_{T - 1}^{(2)j} - \lambda \,x} } \right)} \right. \\ & \quad + \;B_{T + 1} \left( {y + \sum\limits_{j = 1}^{n} {m_{T}^{(T)j} \frac{{P_{T}^{j} + \delta A_{T + 1} m_{T}^{(T)j} }}{{2w_{T}^{j} }}} + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 3}^{T - 1} {m_{T}^{(\tau )j} u_{\tau }^{(4)j} } } + \sum\limits_{j = 1}^{n} {\delta B_{T + 1} \frac{{(b^{j} )^{2} y}}{{2\varepsilon_{T}^{j} }} - \vartheta \,y} } \right) \\ & \left. {\quad + \;\sum\limits_{i = 1}^{n} {p_{T + 1}^{(T)i} \frac{{p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} }}{{2\gamma_{T}^{i} }}} + \sum\limits_{i = 1}^{n} {p_{T + 1}^{(T - 1)i} u_{T - 1}^{(3)i} } + \sum\limits_{i = 1}^{n} {\varpi_{T + 1}^{i} } } \right]\delta^{T} . \\ \end{aligned} $$
(C.4)

Both the left-hand side and right-hand side of (C.4) are linear functions of \( x \) and \( y \). For (C.4) to hold, it is required that:

$$ \begin{aligned} A_{T} & = \sum\limits_{i = 1}^{n} {\alpha_{T}^{i} + A_{T + 1} (1 - \lambda )\delta ,} \\ B_{T} & = \sum\limits_{i = 1}^{n} {\left[ { - \varepsilon_{T}^{i} \left( {\frac{{\delta B_{T + 1} b^{i} }}{{2\varepsilon_{T}^{i} }}} \right)^{2} - h_{T}^{i} } \right]} + \left[ {B_{T + 1} \left( {1 + \sum\limits_{j = 1}^{n} {b_{{}}^{j} } \frac{{\delta B_{T + 1} b^{j} }}{{2\varepsilon_{T}^{j} }} - \vartheta \,} \right)} \right]\delta , \\ \end{aligned} $$
(C.5)

and \( C_{T}^{{}} \) is an expression involving previously executed controls \( \underline{u}_{T - }^{(2)} ,\underline{u}_{T - }^{(3)} ,\underline{u}_{T - }^{(4)} \) which can be expressed as:

$$ \begin{aligned} C_{T} & = \sum\limits_{i = 1}^{n} {\left[ { - c_{T}^{i} \left( {\frac{{\delta A_{T + 1} a_{T}^{(T)i} }}{{2c_{T}^{i} }}} \right)^{2} - \gamma_{T}^{i} \left( {\frac{{p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} }}{{2\gamma_{T}^{i} }}} \right)^{2} + p_{T}^{(T)i} \left( {\frac{{p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} }}{{2\gamma_{T}^{i} }}} \right)} \right.} \\ & \left. {\quad + \;\sum\limits_{\tau = T - 2}^{T - 1} {p_{T}^{(\tau )i} u_{\tau }^{(3)i} } + P_{T}^{i} \left( {\frac{{P_{T}^{i} + \delta A_{T + 1}^{{}} m_{T}^{(T)i} }}{{2w_{T}^{i} }}} \right) - w_{T}^{i} \left( {\frac{{P_{T}^{i} + \delta A_{T + 1}^{{}} m_{T}^{(T)i} }}{{2w_{T}^{i} }}} \right)^{2} } \right] \\ & \quad + \;\left[ {A_{T + 1} \left( {\sum\limits_{j = 1}^{n} {a_{T}^{(T)j} \left( {\frac{{\delta A_{T + 1} a_{T}^{(T)j} }}{{2c_{T}^{j} }}} \right)} + \sum\limits_{j = 1}^{n} {a_{T}^{(T - 1)j} u_{T - 1}^{(2)j} } } \right)} \right. \\ & \quad + \;B_{T + 1} \left( {\sum\limits_{j = 1}^{n} {m_{T}^{(T)j} \frac{{P_{T}^{j} + \delta A_{T + 1}^{{}} m_{T}^{(T)j} }}{{2w_{T}^{j} }}} + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 3}^{T - 1} {} m_{T}^{(\tau )j} u_{\tau }^{(4)j} } } \right) \\ & \left. {\quad + \;\sum\limits_{i = 1}^{n} {p_{T + 1}^{(T)i} \frac{{p_{T}^{(T)i} + \delta {\kern 1pt} p_{T + 1}^{(T)i} }}{{2\gamma_{T}^{i} }}} + \sum\limits_{i = 1}^{n} {p_{T + 1}^{(T - 1)i} u_{T - 1}^{(3)i} } + \sum\limits_{i = 1}^{n} {\varpi_{T + 1}^{i} } } \right]\delta \\ & = \;\varOmega_{T} + \sum\limits_{i = 1}^{n} {\sum\limits_{\tau = T - 2}^{T - 1} {p_{T}^{(\tau )i} u_{\tau }^{(3)i} } } + \delta A_{T + 1} \sum\limits_{j = 1}^{n} {a_{T}^{(T - 1)j} u_{T - 1}^{(2)j} } + \delta B_{T + 1} \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 3}^{T - 1} {m_{T}^{(\tau )j} u_{\tau }^{(4)j} } } \\ & \quad + \;\delta \sum\limits_{i = 1}^{n} {p_{T + 1}^{(T - 1)i} u_{T - 1}^{(3)i} } . \\ \end{aligned} $$
(C.6)

Then, we move to the problem in stage \( T - 1 \). Using \( W(T,x,y;\underline{u}_{T - }^{(2)} ,\underline{u}_{T - }^{(3)} ,\underline{u}_{T - }^{(4)} ) \) in (C.4), the \( T - 1 \) stage equation in (4.6) can be expressed as

$$ \begin{aligned} W\left( {T - 1,x,y;\underline{u}_{(T - 1) - }^{(2)} ,\underline{u}_{(T - 1) - }^{(3)} ,\underline{u}_{(T - 1) - }^{(4)} } \right) & = \mathop {\hbox{max} }\limits_{\substack{ u_{T - 1}^{(1)i} ,u_{T - 1}^{(2)i} ,\,u_{T - 1}^{(3)i} ,u_{T - 1}^{(4)i} \\ i \in N\; } } \left\{ {\sum\limits_{i = 1}^{n} {\left( {\alpha_{T - 1}^{i} x - c_{T - 1}^{i} \left( {u_{T - 1}^{(2)i} } \right)^{2} } \right.} } \right. \\ & \quad \left. { - \;\gamma_{T - 1}^{i} \left( {u_{T - 1}^{(3)i} } \right)^{2} + \sum\limits_{\tau = T - 3}^{T - 1} {p_{T - 1}^{(\tau )i} u_{\tau }^{(3)i} } + \left[ {P_{T - 1}^{i} u_{T - 1}^{(4)i} - w_{T - 1}^{i} (u_{T - 1}^{(4)i} )^{2} } \right] - \varepsilon_{T - 1}^{i} \left( {u_{T - 1}^{(1)i} } \right)^{2} - h_{T - 1}^{i} y} \right)\delta^{T - 2} \\ & \left. {\quad + \;\left( {A_{T} x + B_{T} y + C_{T} } \right)\delta^{T - 1} } \right\}, \\ \end{aligned} $$
(C.7)

where \( x_{T} = x + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 2}^{T - 1} {a_{T - 1}^{(\tau )j} u_{\tau }^{(2)j} } - \lambda \,x} , \)\( y_{T} = y + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 4}^{T - 1} {m_{T - 1}^{(\tau )j} u_{\tau }^{(4)j} } } - \sum\limits_{j = 1}^{n} {b^{j} u_{T - 1}^{(1)j} } (y)^{1/2} - \vartheta \,y. \)

Performing the indicated maximization in (C.7) yields the optimal cooperative strategies:

$$ \begin{aligned} u_{T - 1}^{(1)i} & = \frac{{ - B_{T}^{{}} b_{{}}^{i} (y)^{1/2} \delta }}{{2\varepsilon_{T - 1}^{i} }}, \\ u_{T - 1}^{(2)i} & = \frac{{\delta A_{T} a_{T - 1}^{(T - 1)i} + \delta^{2} A_{T + 1} a_{T}^{(T - 1)i} }}{{2c_{T - 1}^{i} }}, \\ u_{T - 1}^{(3)i} & = \frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }},\;{\text{and}} \\ u_{T - 1}^{(4)i} & = \frac{{P_{T - 1}^{i} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)i} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)i} }}{{2w_{T - 1}^{i} }},\;i \in N. \\ \end{aligned} $$
(C.8)

Invoking “Proposition 4.1” and substituting (C.8) into the stage \( T - 1 \) equation in (4.6), we obtain:

$$ \begin{aligned} W(T - 1,x,y;\underline{u}_{(T - 1) - }^{(2)} ,\underline{u}_{(T - 1) - }^{(3)} ,\underline{u}_{(T - 1) - }^{(4)} ) & = (A_{T - 1}^{{}} x + B_{T - 1}^{{}} y + C_{T - 1}^{{}} )\delta^{T - 2} \\ & = \;\sum\limits_{i = 1}^{n} {} \left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\alpha_{T - 1}^{i} x - c_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta A_{T}^{{}} a_{T - 1}^{(T - 1)i} + \delta^{2} A_{T + 1}^{{}} a_{T}^{(T - 1)i} }}{{2c_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} \\ & \quad - \;\gamma_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} + p_{T - 1}^{(T - 1)} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;\sum\limits_{\tau = T - 3}^{T - 2} {} p_{T - 1}^{(\tau )i} u_{\tau }^{(3)i} + P_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{P_{T - 1}^{i} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)i} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)i} }}{{2w_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad - \;w_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{P_{T - 1}^{i} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)i} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)i} }}{{2w_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} - \varepsilon_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{B_{T}^{{}} b_{{}}^{i} (y)^{1/2} \delta }}{{2\varepsilon_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} - h_{T - 1}^{i} y\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right]\delta^{T - 2} \\ & \quad + \;\left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.A_{T}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.x + \sum\limits_{j = 1}^{n} {a_{T - 1}^{(T - 1)j} } \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta A_{T}^{{}} a_{T - 1}^{(T - 1)j} + \delta^{2} A_{T + 1}^{{}} a_{T}^{(T - 1)j} }}{{2c_{T - 1}^{j} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) + \sum\limits_{j = 1}^{n} {} a_{T - 1}^{(T - 2)j} u_{T - 2}^{(2)j} - \lambda \,x\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;B_{T}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.y + \sum\limits_{j = 1}^{n} {} m_{T - 1}^{(T - 1)j} \frac{{P_{T - 1}^{j} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)j} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)j} }}{{2w_{T - 1}^{j} }} \\ & \quad + \;\sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 4}^{T - 2} {} m_{T - 1}^{(\tau )j} u_{\tau }^{(4)j} } + \sum\limits_{j = 1}^{n} {} \delta B_{T}^{{}} \frac{{(b_{{}}^{j} )^{2} y}}{{2\varepsilon_{T - 1}^{j} }} - \vartheta \,y\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;\left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\varOmega_{T}^{{}} + \sum\limits_{i = 1}^{n} {} p_{T}^{(T - 1)i} \frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }} + \sum\limits_{i = 1}^{n} {} p_{T}^{(T - 2)i} u_{T - 2}^{(3)i} \\ & \quad + \;\delta A_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {} a_{T}^{(T - 1)j} \frac{{\delta A_{T}^{{}} a_{T - 1}^{(T - 1)j} + \delta^{2} A_{T + 1}^{{}} a_{T}^{(T - 1)j} }}{{2c_{T - 1}^{j} }} \\ & \quad + \;\delta B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {m_{T}^{(T - 1)j} } \frac{{P_{T - 1}^{j} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)j} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)j} }}{{2w_{T - 1}^{j} }} + \delta B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} \begin{aligned} \sum\limits_{\tau = T - 3}^{T - 2} {} m_{T}^{(\tau )j} u_{\tau }^{(4)j} \hfill \\ \hfill \\ \end{aligned} \\ & \quad + \;\delta \sum\limits_{i = 1}^{n} {} p_{T + 1}^{(T - 1)i} \frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right]\delta^{T - 1} . \\ \end{aligned} $$
(C.9)

Both the left-hand side and right-hand side of (C.9) are linear functions of \( x \) and \( y \). For (C.9) to hold, it is required that:

$$ \begin{aligned} A_{T - 1}^{{}} & = \sum\limits_{i = 1}^{n} {} \alpha_{T - 1}^{i} + A_{T}^{{}} (1 - \lambda )\delta , \\ B_{T - 1}^{{}} & = \sum\limits_{i = 1}^{n} {} \left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right. - \varepsilon_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta B_{T}^{{}} b_{{}}^{i} }}{{2\varepsilon_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} - h_{T - 1}^{i} \left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right] + \left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.B_{T}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.1 + \sum\limits_{j = 1}^{n} {b_{{}}^{j} } \frac{{\delta B_{T}^{{}} b_{{}}^{j} }}{{2\varepsilon_{T - 1}^{j} }} - \vartheta \,\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right]\delta , \\ \end{aligned} $$
(C.10)

and \( C_{T - 1}^{{}} \) is an expression involving previously executed controls \( \underline{u}_{(T - 1) - }^{(2)} ,\underline{u}_{(T - 1) - }^{(3)} ,\underline{u}_{(T - 1) - }^{(4)} \) which can be expressed as:

$$ \begin{aligned} C_{T - 1}^{{}} & = \;\sum\limits_{i = 1}^{n} {} \left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right. - c_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta A_{T}^{{}} a_{T - 1}^{(T - 1)i} + \delta^{2} A_{T + 1}^{{}} a_{T}^{(T - 1)i} }}{{2c_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} \\ & \quad - \;\gamma_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} + p_{T - 1}^{(T - 1)} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;\sum\limits_{\tau = T - 3}^{T - 2} {} p_{T - 1}^{(\tau )i} u_{\tau }^{(3)i} + P_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{P_{T - 1}^{i} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)i} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)i} }}{{2w_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad - \;w_{T - 1}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{P_{T - 1}^{i} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)i} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)i} }}{{2w_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} \left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right] \\ & \quad + \;\left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.A_{T}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\sum\limits_{j = 1}^{n} {a_{T - 1}^{(T - 1)j} } \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta A_{T}^{{}} a_{T - 1}^{(T - 1)j} + \delta^{2} A_{T + 1}^{{}} a_{T}^{(T - 1)j} }}{{2c_{T - 1}^{j} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) + \sum\limits_{j = 1}^{n} {} a_{T - 1}^{(T - 2)j} u_{T - 2}^{(2)j} \left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;B_{T}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\sum\limits_{j = 1}^{n} {} m_{T - 1}^{(T - 1)j} \frac{{P_{T - 1}^{j} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)j} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)j} }}{{2w_{T - 1}^{j} }} + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 4}^{T - 2} {} m_{T - 1}^{(\tau )j} u_{\tau }^{(4)j} \left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)} \\ & \quad + \;\left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\varOmega_{T}^{{}} + \sum\limits_{i = 1}^{n} {} p_{T}^{(T - 1)i} \frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }} + \sum\limits_{i = 1}^{n} {} p_{T}^{(T - 2)i} u_{T - 2}^{(3)i} \\ & \quad + \;\delta A_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {} a_{T}^{(T - 1)j} \frac{{\delta A_{T}^{{}} a_{T - 1}^{(T - 1)j} + \delta^{2} A_{T + 1}^{{}} a_{T}^{(T - 1)j} }}{{2c_{T - 1}^{j} }} \\ & \quad + \;\delta B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {m_{T}^{(T - 1)j} } \frac{{P_{T - 1}^{j} + \delta B_{T}^{{}} m_{T - 1}^{(T - 1)j} + \delta^{2} B_{T + 1}^{{}} m_{T}^{(T - 1)j} }}{{2w_{T - 1}^{j} }} + \delta B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 3}^{T - 2} {} m_{T}^{(\tau )j} u_{\tau }^{(4)j} } \\ & \quad + \;\delta \sum\limits_{i = 1}^{n} {} p_{T + 1}^{(T - 1)i} \frac{{p_{T - 1}^{(T - 1)i} + \delta {\kern 1pt} p_{T}^{(T - 1)i} + \delta^{2} {\kern 1pt} p_{T + 1}^{(T - 1)i} }}{{2\gamma_{T - 1}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right]\delta \\ & = \;\varOmega_{T - 1}^{{}} + \sum\limits_{i = 1}^{n} {} \sum\limits_{\tau = T - 3}^{T - 2} {} p_{T - 1}^{(\tau )i} u_{\tau }^{(3)i} + \delta A_{T}^{{}} \sum\limits_{j = 1}^{n} {} a_{T - 1}^{(T - 2)j} u_{T - 2}^{(2)j} + \delta B_{T} \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 4}^{T - 2} {} m_{T - 1}^{(\tau )j} u_{\tau }^{(4)j} } \\ & \quad + \;\delta \sum\limits_{i = 1}^{n} {} p_{T}^{(T - 2)i} u_{T - 2}^{(3)i} + \delta^{2} B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 3}^{T - 2} {} m_{T}^{(\tau )j} u_{\tau }^{(4)j} } . \\ \end{aligned} $$
(C.11)

Then, we move to the problem in stage \( T - 2 \). Using \( W(T - 1,x,y;\underline{u}_{(T - 1) - }^{(2)} ,\underline{u}_{(T - 1) - }^{(3)} ,\underline{u}_{(T - 1) - }^{(4)} ) \) in (C.9), the \( T - 2 \) stage equation in (4.6) can be expressed as

$$ \begin{aligned} W(T - 2,x,y;\underline{u}_{(T - 2) - }^{(2)} ,\underline{u}_{(T - 2) - }^{(3)} ,\underline{u}_{(T - 2) - }^{(4)} ) & = \mathop {\hbox{max} }\limits_{\substack{ u_{T - 2}^{(1)i} ,u_{T - 2}^{(2)i} ,\,u_{T - 2}^{(3)i} ,u_{T - 2}^{(4)i} \\ i \in N\; } } \left\{ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\sum\limits_{i = 1}^{n} {\left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.} \alpha_{T - 2}^{i} x - c_{T - 2}^{i} (u_{T - 2}^{(2)i} )^{2} \\ & \quad - \;\gamma_{T - 2}^{i} (u_{T - 2}^{(3)i} )^{2} + \sum\limits_{\tau = T - 4}^{T - 2} {} p_{T - 2}^{(\tau )i} u_{\tau }^{(3)i} + [P_{T - 2}^{i} u_{T - 2}^{(4)i} - w_{T - 2}^{i} (u_{T - 2}^{(4)i} )^{2} ] - \varepsilon_{T - 2}^{i} (u_{T - 2}^{(1)i} )^{2} - h_{T - 2}^{i} y\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)\delta^{T - 2} \\ & \quad + \;(A_{T - 1}^{{}} x + B_{T - 1}^{{}} y + C_{T - 1}^{{}} )\delta^{T - 2} \left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right\}, \\ \end{aligned} $$
(C.12)

where \( x_{T - 1}^{{}} = x + \sum\limits_{j = 1}^{n} {} \sum\limits_{\tau = T - 3}^{T - 2} {a_{T - 2}^{(\tau )j} u_{\tau }^{(2)j} } - \lambda \,x \),\( y_{T - 1}^{{}} = y + \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 5}^{T - 2} {} m_{T - 2}^{(\tau )j} u_{\tau }^{(4)j} } - \sum\limits_{j = 1}^{n} {b_{{}}^{j} u_{T - 2}^{(1)j} } (y)^{1/2} - \vartheta \,y \).

Performing the indicated maximization in (C.12) yields the optimal cooperative strategies:

$$ \begin{aligned} u_{T - 2}^{(1)i} & = \frac{{ - B_{T - 1}^{{}} b_{{}}^{i} (y)^{1/2} \delta }}{{2\varepsilon_{T - 2}^{i} }}, \\ u_{T - 2}^{(2)i} & = \frac{{\delta A_{T - 1}^{{}} a_{T - 2}^{(T - 2)i} + \delta^{2} A_{T}^{{}} a_{T - 1}^{(T - 2)i} }}{{2c_{T - 2}^{i} }}, \\ u_{T - 2}^{(3)i} & = \frac{{p_{T - 2}^{(T - 2)i} + \delta {\kern 1pt} p_{T - 1}^{(T - 2)i} + \delta^{2} {\kern 1pt} p_{T}^{(T - 2)i} }}{{2\gamma_{T - 2}^{i} }},\;{\text{and}} \\ u_{T - 2}^{(4)i} & = \frac{{P_{T - 2}^{i} + \delta B_{T - 1}^{{}} m_{T - 2}^{(T - 2)i} + \delta^{2} B_{T}^{{}} m_{T - 1}^{(T - 2)i} + \delta^{3} B_{T + 1}^{{}} m_{T}^{(T - 2)i} }}{{2w_{T - 2}^{i} }},i \in N. \\ \end{aligned} $$
(C.13)

Invoking Proposition 4.1 and substituting (C.13) into the stage \( T - 2 \) equation in (4.6), we obtain:

$$ \begin{aligned} W(T - 2,x,y;\underline{u}_{(T - 2) - }^{(2)} ,\underline{u}_{(T - 2) - }^{(3)} ,\underline{u}_{(T - 2) - }^{(4)} ) & = (A_{T - 2}^{{}} x + B_{T - 2}^{{}} y + C_{T - 2}^{{}} )\delta^{T - 3} \\ & = \;\sum\limits_{i = 1}^{n} {} \left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\alpha_{T - 2}^{i} x - c_{T - 2}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta A_{T - 1}^{{}} a_{T - 2}^{(T - 2)i} + \delta^{2} A_{T}^{{}} a_{T - 1}^{(T - 2)i} }}{{2c_{T - 2}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} \\ & \quad - \;\gamma_{T - 2}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{p_{T - 2}^{(T - 2)i} + \delta {\kern 1pt} p_{T - 1}^{(T - 2)i} + \delta^{2} {\kern 1pt} p_{T}^{(T - 2)i} }}{{2\gamma_{T - 2}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} + p_{T - 2}^{(T - 2)} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{p_{T - 2}^{(T - 2)i} + \delta {\kern 1pt} p_{T - 1}^{(T - 2)i} + \delta^{2} {\kern 1pt} p_{T}^{(T - 2)i} }}{{2\gamma_{T - 2}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;\sum\limits_{\tau = T - 4}^{T - 3} {} p_{T - 2}^{(\tau )i} u_{\tau }^{(3)i} + P_{T - 2}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{P_{T - 2}^{i} + \delta B_{T - 1}^{{}} m_{T - 2}^{(T - 2)i} + \delta^{2} B_{T}^{{}} m_{T - 1}^{(T - 2)i} + \delta^{3} B_{T + 1}^{{}} m_{T}^{(T - 2)i} }}{{2w_{T - 2}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad - \;w_{T - 2}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{P_{T - 2}^{i} + \delta B_{T - 1}^{{}} m_{T - 2}^{(T - 2)i} + \delta^{2} B_{T}^{{}} m_{T - 1}^{(T - 2)i} + \delta^{3} B_{T + 1}^{{}} m_{T}^{(T - 2)i} }}{{2w_{T - 2}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} \\ & \quad - \;\varepsilon_{T - 2}^{i} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{B_{T - 1}^{{}} b_{{}}^{i} (y)^{1/2} \delta }}{{2\varepsilon_{T - 2}^{i} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)^{2} - h_{T - 2}^{i} y\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right]\delta^{T - 3} \\ & \quad + \;\left[ {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.A_{T - 1}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.x + \sum\limits_{j = 1}^{n} {a_{T - 2}^{(T - 2)j} } \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\frac{{\delta A_{T - 1}^{{}} a_{T - 2}^{(T - 2)j} + \delta^{2} A_{T}^{{}} a_{T - 1}^{(T - 2)j} }}{{2c_{T - 2}^{j} }}\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) + \sum\limits_{j = 1}^{n} {} a_{T - 2}^{(T - 3)j} u_{T - 3}^{(2)j} - \lambda \,x\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;B_{T - 1}^{{}} \left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.y + \sum\limits_{j = 1}^{n} {} m_{T - 2}^{(T - 2)j} \frac{{P_{T - 2}^{j} + \delta B_{T - 1}^{{}} m_{T - 2}^{(T - 2)j} + \delta^{2} B_{T}^{{}} m_{T - 1}^{(T - 2)j} + \delta^{3} B_{T + 1}^{{}} m_{T}^{(T - 2)j} }}{{2w_{T - 2}^{j} }} \\ & \quad + \;\sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 5}^{T - 3} {} m_{T - 2}^{(\tau )j} u_{\tau }^{(4)j} } + \sum\limits_{j = 1}^{n} {} \delta B_{T - 1}^{{}} \frac{{(b_{{}}^{j} )^{2} y}}{{2\varepsilon_{T - 2}^{j} }} - \vartheta \,y\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right) \\ & \quad + \;\left( {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right.\varOmega_{T - 1}^{{}} + \sum\limits_{i = 1}^{n} {} p_{T - 1}^{(T - 2)i} \frac{{p_{T - 2}^{(T - 2)i} + \delta {\kern 1pt} p_{T - 1}^{(T - 2)i} + \delta^{2} {\kern 1pt} p_{T}^{(T - 2)i} }}{{2\gamma_{T - 2}^{i} }} + \sum\limits_{i = 1}^{n} {} p_{T - 1}^{(T - 3)i} u_{T - 3}^{(3)i} \\ & \quad + \;\delta A_{T}^{{}} \sum\limits_{j = 1}^{n} {} a_{T - 1}^{(T - 2)j} \frac{{\delta A_{T - 1}^{{}} a_{T - 2}^{(T - 2)j} + \delta^{2} A_{T}^{{}} a_{T - 1}^{(T - 2)j} }}{{2c_{T - 2}^{j} }} \\ & \quad + \;\delta B_{T} \sum\limits_{j = 1}^{n} {m_{T - 1}^{(T - 2)j} } \frac{{P_{T - 2}^{i} + \delta B_{T - 1}^{{}} m_{T - 2}^{(T - 2)i} + \delta^{2} B_{T}^{{}} m_{T - 1}^{(T - 2)i} + \delta^{3} B_{T + 1}^{{}} m_{T}^{(T - 2)i} }}{{2w_{T - 2}^{i} }} \\ & \quad + \;\delta B_{T} \sum\limits_{j = 1}^{n} {\sum\limits_{\tau = T - 4}^{T - 3} {} m_{T - 1}^{(\tau )j} u_{\tau }^{(4)j} } + \delta \sum\limits_{i = 1}^{n} {} p_{T}^{(T - 2)i} \frac{{p_{T - 2}^{(T - 2)i} + \delta {\kern 1pt} p_{T - 1}^{(T - 2)i} + \delta^{2} {\kern 1pt} p_{T}^{(T - 2)i} }}{{2\gamma_{T - 2}^{i} }} \\ & \quad + \;\delta^{2} B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {m_{T}^{(T - 2)j} } \frac{{P_{T - 2}^{i} + \delta B_{T - 1}^{{}} m_{T - 2}^{(T - 2)i} + \delta^{2} B_{T}^{{}} m_{T - 1}^{(T - 2)i} + \delta^{3} B_{T + 1}^{{}} m_{T}^{(T - 2)i} }}{{2w_{T - 2}^{i} }} \\ & \quad + \;\delta^{2} B_{T + 1}^{{}} \sum\limits_{j = 1}^{n} {m_{T}^{(T - 3)j} u_{T - 3}^{(4)j} } \left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right)\left. {\begin{array}{*{20}c} {} \\ {} \\ \end{array} } \right]\delta_{{}}^{T - 3} . \\ \end{aligned} $$
(C.14)

Both the left-hand side and right-hand side of (C.14) are linear functions of \( x \) and \( y \). For (C.14) to hold, it is required that:

$$ \begin{aligned} A_{T - 2} & = \sum\limits_{i = 1}^{n} {\alpha_{T - 2}^{i} + A_{T - 1} (1 - \lambda )\delta } , \\ B_{T - 2} & = \sum\limits_{i = 1}^{n} {\left[ { - \varepsilon_{T - 2}^{i} \left( {\frac{{\delta B_{T - 1} b_{{}}^{i} }}{{2\varepsilon_{T - 2}^{i} }}} \right)^{2} - h_{T - 2}^{i} } \right]} + \left[ {B_{T - 1} \left( {1 + \sum\limits_{j = 1}^{n} {b^{j} } \frac{{\delta B_{T - 1} b^{j} }}{{2\varepsilon_{T - 2}^{j} }} - \vartheta } \right)} \right]\delta , \\ \end{aligned} $$
(C.15)

and \( C_{T - 2}^{{}} \) is an expression involving previously executed controls \( \underline{u}_{(T - 2) - }^{(2)} ,\underline{u}_{(T - 2) - }^{(3)} ,\underline{u}_{(T - 2) - }^{(4)} \).

We move to the problem in stage \( k \in \{ T - 3,T - 4, \cdots ,1\} \). Following the above analysis, we obtain

$$ \begin{aligned} A_{k} & = \sum\limits_{i = 1}^{n} {\alpha_{k}^{i} + A_{k + 1} (1 - \lambda )\delta } , \\ B_{k} & = \sum\limits_{i = 1}^{n} {\left[ { - \varepsilon_{k}^{i} \left( {\frac{{\delta B_{k + 1} b_{{}}^{i} }}{{2\varepsilon_{k}^{i} }}} \right)^{2} - h_{k}^{i} } \right]} + \left[ {B_{k} \left( {1 + \sum\limits_{j = 1}^{n} {b^{j} } \frac{{\delta B_{k + 1} b^{j} }}{{2\varepsilon_{k}^{j} }} - \vartheta \,} \right)} \right]\delta , \\ \end{aligned} $$
(C.16)

and \( C_{k}^{{}} \) is an expression involving previously executed controls \( \underline{u}_{k - }^{(2)} ,\underline{u}_{k - }^{(3)} ,\underline{u}_{k - }^{(4)} \).

The optimal cooperative strategies can be obtained as:

$$ \begin{aligned} u_{k}^{(1)i} & = \frac{{ - B_{k + 1} b^{i} (y)^{1/2} \delta }}{{2\varepsilon_{k}^{i} }}, \\ u_{k}^{(2)i} & = \frac{{\delta A_{k + 1} a_{k}^{(k)i} + \delta^{2} A_{k + 2} a_{k + 1}^{(k)i} }}{{2c_{k}^{i} }}, \\ u_{k}^{(3)i} & = \frac{{p_{k}^{(k)i} + \delta {\kern 1pt} p_{k + 1}^{(k)i} + \delta^{2} {\kern 1pt} p_{k + 2}^{(k)i} }}{{2\gamma_{k}^{i} }},{\text{and}} \\ u_{k}^{(4)i} & = \frac{{P_{k}^{i} + \delta B_{k + 1} m_{k}^{(k)i} + \delta^{2} B_{k + 2} m_{k + 1}^{(k)i} + \delta^{3} B_{k + 3} m_{k + 2}^{(k)i} + \delta^{4} B_{k + 4} m_{k + 3}^{(k)i} }}{{2w_{T - 2}^{i} }}, \\ \end{aligned} $$
(C.17)

for \( i \in N \) and \( k \in \{ T - 3,T - 4, \cdots ,1\} \).

For notational convenience, we specify \( A_{T + 2}^{{}} = 0 \), \( {\kern 1pt} p_{T + 2}^{(T)i} = 0 \) and \( B_{T + 2}^{{}} = B_{T + 3}^{{}} = B_{T + 4}^{{}} = 0 \). Then, the optimal cooperative strategies, for \( k \in \{ 1,2, \cdots ,T\} \), can be expressed as in (C.17).□

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Petrosyan, L.A., Yeung, D.W. Cooperative Dynamic Games with Durable Controls: Theory and Application. Dyn Games Appl 10, 872–896 (2020). https://doi.org/10.1007/s13235-019-00336-w

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