Skip to main content
Log in

Minimal farsighted instability

  • Original Paper
  • Published:
International Journal of Game Theory Aims and scope Submit manuscript

Abstract

We propose the notion of minimal farsighted instability to determine the states that are more likely to emerge in the long run when agents are farsighted. A state is minimally farsighted unstable if there is no other state which is more farsightedly stable. To formulate what it means to be more farsightedly stable, we compare states by comparing (in the set inclusion or cardinal sense) their sets of farsighted defeating states. We next compare states in terms of their absorbtiveness by comparing both their sets of farsighted defeating states (i.e. in terms of their stability) and their sets of farsighted defeated states (i.e. in terms of their reachability). A state is maximally farsighted absorbing if there is no other state which is more farsightedly absorbing. We provide general results for characterizing minimally farsighted unstable states and maximally farsighted absorbing states, and we study their relationships with alternative notions of farsightedness. Finally, we use experimental data to show the relevance of the new solution concepts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. Jackson (2008) defines the notion of farsightedly pairwise stable network: a network is a farsightedly pairwise stable network if and only if it is not farsightedly defeated.

  2. The set of farsighted defeating states of a given state is the set of all states that farsightedly defeat this state.

  3. The existence of a farsighted improving path means that some agents could leave the current state anticipating further deviations from other agents leading to a final state, where all the agents deviating along the path are better off than at the current state when they deviate. Thus, it is a potential source of instability. And the higher the number of farsighted improving paths emanating from a state, the higher the potential instability of such state.

  4. Minimally unstable assignments (in the set inclusion sense) are considered by Abdulkadiroğlu et al. (2020) and Tang and Zhang (2021) for school choice problems and by Combe et al. (2022) for teacher assignment problems.

  5. The set of farsighted defeated states of a given state is the set of all states that this state farsightedly defeats.

  6. Alternative notions of farsightedness are suggested by Bloch and van den Nouweland (2020); Diamantoudi and Xue (2003); Dutta et al. (2005); Dutta and Vohra (2017); Ray and Vohra (2019); Herings et al. (2004); Kimya (2020); Mauleon and Vannetelbosch (2004); Page and Wooders (2009); Xue (1998) among others.

  7. Throughout the paper we use the notation \(\subseteq \) for weak inclusion and \(\varsubsetneq \) for strict inclusion. Finally, \(\#\) will refer to the notion of cardinality.

  8. Mauleon and Vannetelbosch (2016) provide a comprehensive overview of the solution concepts for solving network formation games.

  9. The notion of farsighted improving path is introduced by Jackson (2008) and Herings et al. (2009) in network formation, Herings et al. (2010) in coalition formation, and Mauleon et al. (2022) in normal-form games. Jackson and Watts (2002) define the notion of improving path in network formation when all players are myopic. Herings et al. (2020); Luo et al. (2021) and Mauleon et al. (2022) extend this notion to a mixed population composed of both myopic and farsighted players in matching markets, network formation problems and coordination games, respectively.

  10. Diamantoudi and Xue (2003) study the farsighted core in hedonic games.

  11. Mauleon et al. (2022) show that there always exists a farsightedly stable strategy profile in coordination games but, in general, there is no guarantee that there exist farsightedly stable strategy profiles.

  12. Take \(b(1)=3\), \(b(2)=1.5\), \(b(3)=0.5\), \(c=2\) and \(n=4\). Computing the number of defeating networks (\(\#\phi (g)\)) and number of defeated networks (\(\#\phi ^{-1}(g))\)) for each network, we obtain that \(F_{\#}= \{g \in {\mathcal {G}} \mid g \text { is a 2-regular network}\}\) while \(A_{\#} = \{g \in {\mathcal {G}} \mid g \text { is a star network}\} \cup \{g \in {\mathcal {G}} \mid g \text { is a 2-regular network}\}\).

  13. See Luo et al. (2021).

  14. Herings et al. (2020) and Luo et al. (2021) define the notion of myopic-farsighted stable set that extends the notion of vNM farsighted stable set to a mixed population of myopic and farsighted players.

  15. Herings et al. (2009, 2010) introduce the DEM farsighted stable set for network formation and coalition formation problems.

  16. Mauleon and Vannetelbosch (2004) define the largest (cautious) consistent set for coalition formation problems while Herings et al. (2009) define the largest pairwise consistent set for network formation problems (see also Page et al. 2005).

  17. The design of the termination rule allows each individual to decide unilaterally to continue playing (at least for the first 26 stages).

  18. Since the empty network is pairwise stable in all treatments, myopia predicts the empty network in T1, T2 and T3.

  19. From the experimental data, we only have the number of groups ending in each class in the experiment. The average number of groups ending in any given network is then equal to the number of groups ending in each class divided by the number of different networks in the class.

  20. There are four different networks in class \(C_{5}\). In total 53.6% of the groups end up in class \(C_{5}\).

  21. In the column T3* the percentage is computed considering the number of payoff relevant networks in each class. For instance, the number of groups ending on average in a representative network of class \(C_{7}\) becomes 3% (instead of 1.5% in Table 3) since there are only 6 different payoff relevant networks in this class.

  22. With respect to the first criteria, FSS is (weakly) dominated by F, and with respect to the second criteria, FSS is (weakly) dominated by \(F_{\#}\).

  23. When we separate the classes of networks between those with a frequency higher than \(1\%\) and the others, F (and \(A_{\#}\)) has the highest correlation with this binary criteria.

  24. An alternative approach for solving the lack of farsighted stability is to require the consent of partners or neighbours for adding or deleting links. See (Caulier et al. 2013) and (Caulier et al. 2013).

  25. Notice that the vNM farsighted stable set is also based on the notion of farsighted improving path, given by the correspondence \(\phi (x)\), that ignores the possibility that one might avoid enforcing a new state that is valuable to her anticipating further changes making her worse off. This drawback was already pointed out by Chwe (1994) and partially solved by the largest consistent set and the DEM farsighted stable set.

References

  • Abdulkadiroğlu A, Che YK, Pathak PA, Roth AE, Tercieux O (2020) Efficiency, justified envy, and incentives in priority-based matching. Am Econ Rev Insights 2(4):425–442

    Article  Google Scholar 

  • Bloch F, Jackson MO (2007) The formation of networks with transfers among players. J Econ Theory 133:83–110

    Article  MathSciNet  Google Scholar 

  • Bloch F, van den Nouweland A (2020) Farsighted stability with heterogeneous expectations. Games Econ Behav 121:32–54

    Article  MathSciNet  Google Scholar 

  • Caulier J-F, Mauleon A, Vannetelbosch V (2013) Contractually stable networks. Int J Game Theory 42:483–499

    Article  MathSciNet  Google Scholar 

  • Caulier J-F, Mauleon A, Sempere-Monerris JJ, Vannetelbosch V (2013) Stable and efficient coalitional networks. Rev Econ Des 17:249–271

    MathSciNet  Google Scholar 

  • Chwe MS (1994) Farsighted coalitional stability. J Econ Theory 63:299–325

    Article  ADS  MathSciNet  Google Scholar 

  • Combe J, Tercieux O, Terrier C (2022) The design of teacher assignment: theory and evidence. Rev Econ Stud 89:3154–3222

    Article  MathSciNet  Google Scholar 

  • Diamantoudi E, Xue L (2003) Farsighted stability in hedonic games. Social Choice Welf 21:39–61

    Article  MathSciNet  Google Scholar 

  • Doğan B, Ehlers L (2021) Minimally unstable Pareto improvements over deferred acceptance. Theor Econ 16:1249–1279

    Article  MathSciNet  Google Scholar 

  • Doğan B, Ehlers L (2022) Robust minimal instability of the top trading cycles mechanism. Am Econ J Microecon 14:556–82

    Article  Google Scholar 

  • Dutta B, Ghosal S, Ray D (2005) Farsighted network formation. J Econ Theory 122:143–164

    Article  MathSciNet  Google Scholar 

  • Dutta B, Vohra R (2017) Rational expectations and farsighted stability. Theor Econ 12:1191–1227

    Article  MathSciNet  Google Scholar 

  • Grandjean G, Mauleon A, Vannetelbosch V (2011) Connections among farsighted agents. J Public Econ Theory 13(6):935–955

    Article  Google Scholar 

  • Herings PJJ, Mauleon A, Vannetelbosch V (2004) Rationalizability for social environments. Games Econ Behav 49:135–156

    Article  MathSciNet  Google Scholar 

  • Herings PJJ, Mauleon A, Vannetelbosch V (2009) Farsightedly stable networks. Games Econ Behav 67:526–541

    Article  MathSciNet  Google Scholar 

  • Herings PJJ, Mauleon A, Vannetelbosch V (2010) Coalition formation among farsighted agents. Games 1:286–298

    Article  MathSciNet  Google Scholar 

  • Herings PJJ, Mauleon A, Vannetelbosch V (2019) Stability of networks under horizon-\(K\) farsightedness. Econ Theory 68:177–201

    Article  MathSciNet  Google Scholar 

  • Herings PJJ, Mauleon A, Vannetelbosch V (2020) Matching with myopic and farsighted players. J Econ Theory 190:105125

    Article  MathSciNet  Google Scholar 

  • Jackson MO (2008) Social and economic networks. Princeton University Press, Princeton, NJ, USA

    Book  Google Scholar 

  • Jackson MO, Watts A (2002) The evolution of social and economic networks. J Econ Theory 106:265–295

    Article  MathSciNet  Google Scholar 

  • Jackson MO, Wolinsky A (1996) A strategic model of social and economic networks. J Econ Theory 71:44–74

    Article  MathSciNet  Google Scholar 

  • Kimya M (2020) Equilibrium coalition behavior. Theor Econ 15:669–714

    Article  ADS  MathSciNet  Google Scholar 

  • Kirchsteiger G, Mantovani M, Mauleon A, Vannetelbosch V (2016) Limited farsightedness in network formation. J Econ Behav Organ 128:97–120

    Article  Google Scholar 

  • Luo C, Mauleon A, Vannetelbosch V (2021) Network formation with myopic and farsighted players. Econ Theory 71:1283–1317

    Article  MathSciNet  Google Scholar 

  • Mauleon A, Schopohl S, Taalaibekova A, Vannetelbosch V (2022) Coordination on networks with farsighted and myopic agents. Int J Game Theory 51:509–536

    Article  MathSciNet  Google Scholar 

  • Mauleon A, Vannetelbosch V (2004) Farsightedness and cautiousness in coalition formation games with positive spillovers. Theory Decis 56:291–324

    Article  MathSciNet  Google Scholar 

  • Mauleon A, Vannetelbosch V (2016) Network formation games. In: Bramoullé Y, Galeotti A, Rogers BW (eds) The Oxford Handbook of the Economics of Networks. Oxford University Press, UK

    Google Scholar 

  • Mauleon A, Vannetelbosch V, Vergote W (2011) von Neumann Morgernstern farsightedly stable sets in two-sided matching. Theor Econ 6:499–521

    Article  MathSciNet  Google Scholar 

  • Page FH Jr, Wooders M, Kamat S (2005) Networks and farsighted stability. J Econ Theory 120:257–269

    Article  MathSciNet  Google Scholar 

  • Page FH Jr, Wooders M (2009) Strategic basins of attraction, the path dominance core, and network formation games. Games Econ Behav 66:462–487

    Article  MathSciNet  Google Scholar 

  • Ray D, Vohra R (2015) The farsighted stable set. Econometrica 83:977–1011

    Article  MathSciNet  Google Scholar 

  • Ray D, Vohra R (2019) Maximality in the farsighted stable set. Econometrica 87(5):1763–1779

    Article  MathSciNet  Google Scholar 

  • Tang Q, Zhang Y (2021) Weak stability and Pareto efficiency in school choice. Econ Theory 71:533–552

    Article  MathSciNet  Google Scholar 

  • Xue L (1998) Coalitional stability under perfect foresight. Econ Theory 11:603–627

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

Ana Mauleon and Vincent Vannetelbosch are, respectively, Research Director and Senior Research Associate of the National Fund for Scientific Research (FNRS). Financial support from the Fonds de la Recherche Scientifique - FNRS research grant T.0143.18 is gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Vincent Vannetelbosch.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

1.1 Experimental data

Let \(g^{i}\) be a generic network in class \(C_{i}\) and \(c_{i}\subseteq C_{i}\) a generic proper subset of the corresponding class. We will write \( g^{i}\rightarrow g\) with \(g\in C_{j}\), and \(g^{i}\rightarrow g\) with \(g\in c_{j}\), when the generic network \(g^{i}\) in class \(C_{i}\) reaches with a farsighted improving path all the networks in class \(C_{j}\) or only a proper subset \(c_{j}\) of \(C_{j}\), respectively.

Table 8 Number of defeating networks (\(\#\phi (g)\)) and number of defeated networks (\(\#\phi ^{-1}(g)\)) for each network in each class of networks of the experiment

1.1.1 Minimally unstable and maximally absorbing networks in T1

In treatment 1 (T1) the set of networks that can be reached from \(g^{i}\) by some farsighted improving path are:

$$\begin{aligned} \phi (g^{\emptyset })= & {} \left\{ g\mid g\in C_{10}\cup C_{11}\right\} \\ \phi (g^{2})= & {} \left\{ g\mid g\in C_{1}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{3})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{5}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{4})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{5}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{5})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{6})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup c_{5}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{7})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{3}\cup c_{4}\cup C_{5}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{8})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup C_{5}\cup c_{7}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{9})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup c_{5}\cup c_{6}\cup c_{7}\cup C_{10}\cup C_{11}\right\} \\ \phi (g^{10})= & {} \left\{ g\mid g\in c_{2}\cup c_{4}\cup c_{5}\cup c_{6}\cup C_{11}\right\} \\ \phi (g^{N})= & {} \emptyset . \end{aligned}$$

Remember that a network \(g\in {\mathcal {G}}\) is minimally farsighted unstable if there is no \(g^{\prime }\ne g\) such that \(g^{\prime }\gnsim ^{\sigma (\subseteq )}g\); i.e., \(\phi (g^{\prime })\varsubsetneq \phi (g)\). It follows that \(g^{N}\) is the unique minimally farsighted unstable network. Notice that \(g^{\emptyset }\) is more farsightedly stable than all networks \(g\ne g^{10},g^{N}\).

A network \(g\in {\mathcal {G}}\) is maximally farsighted absorbing if there is no \(g^{\prime }\ne g\) such that \(g^{\prime }\gnsim ^{\alpha (\subseteq )}g\); i.e., \(\phi (g^{\prime })\subseteq \phi (g)\) and \(\phi ^{-1}(g)\subseteq \phi ^{-1}(g^{\prime })\) with one inclusion holding strictly. Since \(\phi (g^{N})=\emptyset \) and \(g^{N}\in \phi (g^{i})\) for all \(g^{i}\ne g^{N}\), it also holds that \(g^{N}\) is the unique maximally farsighted absorbing network.

A network \(g\in {\mathcal {G}}\) is \(\#\)-minimally farsighted unstable if there is no \(g^{\prime }\ne g\) such that \(g^{\prime }\gnsim ^{\sigma (\#)}g\); i.e., \(\#\phi (g^{\prime }) < \#\phi (g)\). Thus, \(g^{N}\) is the \(\#\)-minimally farsighted unstable network.

A network \(g\in {\mathcal {G}}\) is \(\#\)-maximally farsighted absorbing if there is no \(g^{\prime }\ne g\) such that \(g^{\prime }\gnsim ^{\alpha (\#)}g\); i.e., \(\#\phi (g^{\prime })\le \#\phi (g)\) and \(\#\phi ^{-1}(g)\le \#\phi ^{-1}(g^{\prime })\) with one inequality holding strictly. Then, \(g^{N}\) is the \(\#\)-maximally farsighted absorbing network.

1.1.2 Minimally unstable and maximally absorbing networks in T2

Let us denote \(B_{g}\) the networks that are adjacent to g,

$$\begin{aligned} B_{g}=\left\{ g^{\prime }\mid g^{\prime }=g+ij\vee g-ij\text {, for some }ij\right\} , \end{aligned}$$

and let \({\overline{B}}_{g}\) be its complement. In treatment 2 (T2) the set of networks that can be reached from \(g^{i}\) by some farsighted improving path are:

$$\begin{aligned} \phi (g^{\emptyset })= & {} \left\{ g\mid g\in C_{5}\right\} \\ \phi (g^{2})= & {} \left\{ g\mid g\in C_{1}\cup C_{5}\cup c_{9}\right\} \\ \phi (g^{3})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup C_{5}\cup C_{9}\right\} \\ \phi (g^{4})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup C_{5}\cup c_{9}\right\} \\ \phi (g^{5})= & {} \left\{ g\mid g\in C_{9}\cap {\overline{B}} _{g^{5}}\right\} \\ \phi (g^{6})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup C_{5}\cup C_{9}\right\} \\ \phi (g^{7})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{3}\cup c_{4}\cup C_{5}\cup C_{9}\right\} \\ \phi (g^{8})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup C_{5}\cup c_{7}\cup C_{9}\right\} \\ \phi (g^{9})= & {} \left\{ g\mid g\in c_{4}\cup (C_{5}\cap B_{g^{9}})\cup (C_{9}\setminus g^{9})\right\} \\ \phi (g^{10})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup C_{5}\cup c_{7}\cup c_{8}\cup C_{9}\right\} \\ \phi (g^{N})= & {} \left\{ g\mid g\in C_{5}\cup C_{9}\cup C_{10}\right\} . \end{aligned}$$

Note that \(g^{\emptyset }\) is more farsightedly stable than all networks \(g\ne g^{5},g^{9}\). Moreover, neither \(g^{5}\) nor \(g^{9}\) are more farsightedly stable than \(g^{\emptyset }\). Thus, \(g^{\emptyset }\) is minimally farsighted unstable. Note also that it is not always true that \((C_{9}{\setminus } g^{9})\supseteq (C_{9}\cap {\overline{B}}_{g^{5}})\) since \(g^{9}\) could belong to \((C_{9}\cap {\overline{B}}_{g^{5}})\). Then, also \(g^{5},g^{9}\) are minimally farsighted unstable.

The maximally farsighted absorbing networks are \(g^{\emptyset },g^{5}\) and \(g^{9}\). Indeed:

$$\begin{aligned} \phi ^{-1}(g^{\emptyset })= & {} \left\{ g\mid g\in C_{2}\cup C_{3}\cup C_{4}\cup C_{6}\cup C_{7}\cup C_{8}\cup C_{10}\right\} ;\\ \phi ^{-1}(g^{5})= & {} \left\{ g\mid g\in C_{1}\cup C_{2}\cup C_{3}\cup C_{4}\cup C_{6}\cup C_{7}\cup C_{8}\cup c_{9}\cup C_{10}\cup C_{11}\right\} \end{aligned}$$

and

$$\begin{aligned} \phi ^{-1}(g^{9})=\left\{ g\mid g\in C_{2}\cup C_{3}\cup C_{4}\cup C_{5}\cup C_{6}\cup C_{7}\cup C_{8}\cup c_{9}\cup C_{10}\cup C_{11}\right\} . \end{aligned}$$

From Table 8, we have that \(g^{\emptyset }\) is the \(\#\)-minimally farsighted unstable network. Notice that the network \(g^{\emptyset }\) is \(\#\)-more farsightedly absorbing than the network \(g^{2}\), but not more than \(g^{5}\) and \(g^{9}\).

1.1.3 Minimally unstable and maximally absorbing networks in T3

In treatment 3 the set of networks that can be reached from \(g^{i}\) by some farsighted improving path are:

$$\begin{aligned} \phi (g^{\emptyset })= & {} \left\{ g\mid g\in C_{7}\right\} \\ \phi (g^{2})= & {} \left\{ g\mid g\in C_{1}\cup C_{7}\cup c_{10}\right\} \\ \phi (g^{3})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup C_{7}\cup C_{10}\right\} \\ \phi (g^{4})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{5}\cup C_{7}\cup c_{10}\right\} \\ \phi (g^{5})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup C_{7}\cup c_{10}\right\} \\ \phi (g^{6})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup c_{5}\cup C_{7}\cup C_{10}\right\} \\ \phi (g^{7})= & {} \left\{ g\mid g\in \left( C_{7}\setminus g\text { s.t. }d_{i}(g)=d_{i}(g^{7})\text { for all }i\in N\right) \cup C_{10}\right\} \\ \phi (g^{8})= & {} \left\{ g\mid g\in C_{1}\cup c_{4}\cup C_{7}\cup C_{10}\right\} \\ \phi (g^{9})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup c_{5}\cup c_{6}\cup C_{7}\cup C_{10}\right\} \\ \phi (g^{10})= & {} \left\{ g\mid g\in C_{1}\cup c_{2}\cup c_{4}\cup c_{5}\cup c_{6}\cup C_{7}\cup c_{8}\cup C_{10}\setminus g^{10}\right\} \\ \phi (g^{11})= & {} \left\{ g\mid g\in C_{7}\cup C_{10}\right\} . \end{aligned}$$

Note that \(g^{\emptyset }\) is more farsightedly stable than all networks \(g\ne g^{7}\). Moreover, \(g^{7}\) is not more farsightedly stable than \(g^{\emptyset }\). Thus, \(g^{\emptyset }\) and each \(g^{7}\) are minimally farsighted unstable networks. The maximally farsighted absorbing networks are also \(g^{\emptyset },g^{7}\) and \(g^{10}\). Indeed:

$$\begin{aligned} \phi ^{-1}(g^{\emptyset })= & {} \left\{ g\mid g\in C_{2}\cup C_{3}\cup C_{4}\cup C_{5}\cup C_{6}\cup C_{8}\cup C_{9}\cup C_{10}\right\} ;\\ \phi ^{-1}(g^{7})= & {} \left\{ g\mid g\in C_{1}\cup C_{2}\cup C_{3}\cup C_{4}\cup C_{5}\cup C_{6}\cup c_{7}\cup C_{8}\cup c_{9}\cup C_{10}\cup C_{11}\right\} \end{aligned}$$

and

$$\begin{aligned} \phi ^{-1}(g^{10})=\left\{ g\mid g\in c_{2}\cup C_{3}\cup c_{4}\cup c_{5}\cup C_{6}\cup C_{7}\cup C_{8}\cup C_{9}\cup C_{10}\setminus g^{10}\cup C_{11}\right\} . \end{aligned}$$

From Table 8, we have that \(g^{\emptyset }\) is the \(\#\)-minimally farsighted unstable network. Remark that the network \(g^{7}\) is \(\#\)-more farsightedly absorbing than all other networks except \(g^{\emptyset }\).

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

de Callataÿ, P., Mauleon, A. & Vannetelbosch, V. Minimal farsighted instability. Int J Game Theory (2024). https://doi.org/10.1007/s00182-024-00887-2

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00182-024-00887-2

Keywords

JEL classification:

Navigation