Capability-Weighted Group Utility Maximizer for Network Coalitional Games under Uncertainty

2012 ◽  
Author(s):  
U. Sridhar ◽  
S. Mandyam
Keyword(s):  
Coalitional Games ◽  
Utility Maximizer

scholarly journals Invariance and randomness in the Nash program for coalitional games

1998 ◽  
Vol 58 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Nir Dagan ◽  
Roberto Serrano
Keyword(s):  
Coalitional Games ◽  
Nash Program

Coalitional Games for Computation Offloading in NOMA-Enabled Multi-Access Edge Computing

2020 ◽  
Vol 69 (2) ◽  
pp. 1982-1993 ◽  
Author(s):  
Quoc-Viet Pham ◽  
Hoang T. Nguyen ◽  
Zhu Han ◽  
Won-Joo Hwang
Keyword(s):  
Edge Computing ◽  
Computation Offloading ◽  
Coalitional Games ◽  
Multi Access

Internal structure of coalitions in competitive and altruistic graphical coalitional games

Automatica ◽  
2014 ◽  
Vol 50 (2) ◽  
pp. 335-348 ◽  
Author(s):  
Muhammad Aurangzeb ◽  
Frank L. Lewis
Keyword(s):  
Internal Structure ◽  
Coalitional Games

Equivalence nucleolus for coalitional games with externalities

2016 ◽  
Vol 44 (2) ◽  
pp. 219-224
Author(s):  
Rajeev R. Tripathi ◽  
R.K. Amit
Keyword(s):  
Coalitional Games ◽  
Games With Externalities

Finite Solution Theory for Coalitional Games

1982 ◽  
Vol 3 (4) ◽  
pp. 551-565 ◽  
Author(s):  
William F. Lucas ◽  
Kai Michaelis
Keyword(s):  
Coalitional Games ◽  
Solution Theory ◽  
Finite Solution

OPTIMAL PORTFOLIO UNDER STATE-DEPENDENT EXPECTED UTILITY

2018 ◽  
Vol 21 (03) ◽  
pp. 1850013 ◽  
Author(s):  
CAROLE BERNARD ◽  
STEVEN VANDUFFEL ◽  
JIANG YE
Keyword(s):  
Portfolio Choice ◽  
Expected Utility ◽  
Loss Aversion ◽  
Reference Point ◽  
Joint Distribution ◽  
Optimal Portfolio ◽  
Characterization Result ◽  
Terminal Wealth ◽  
Utility Maximizer ◽  
State Dependent

We derive the optimal portfolio for an expected utility maximizer whose utility does not only depend on terminal wealth but also on some random benchmark (state-dependent utility). We then apply this result to obtain the optimal portfolio of a loss-averse investor with a random reference point (extending a result of Berkelaar et al. (2004) Optimal portfolio choice under loss aversion, The Review of Economics and Statistics 86 (4), 973–987). Clearly, the optimal portfolio has some joint distribution with the benchmark and we show that it is the cheapest possible in having this distribution. This characterization result allows us to infer the state-dependent utility function that explains the demand for a given (joint) distribution.

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