Sensor Planning with Non-linear Utility Functions

2000 ◽  
pp. 265-277
Author(s):  
Sven Koenig ◽  
Yaxin Liu
Keyword(s):  
Utility Functions ◽  
Sensor Planning ◽  
Non Linear ◽  
Linear Utility ◽  
Linear Utility Functions

scholarly journals A Logit Model with Non-Linear Utility Functions

2003 ◽  
Vol 20 ◽  
pp. 493-500
Author(s):  
Shoichiro NAKAYAMA ◽  
Jun-ichi TAKAYAMA ◽  
Yuichiro YAMASHITA
Keyword(s):  
Logit Model ◽  
Utility Functions ◽  
Non Linear ◽  
Linear Utility ◽  
Linear Utility Functions

scholarly journals The Reinsurer's Monopoly and the Bowley Solution

1985 ◽  
Vol 15 (2) ◽  
pp. 141-148 ◽  
Author(s):  
Fung-Yee Chan ◽  
Hans U. Gerber
Keyword(s):  
Expected Utility ◽  
Random Variable ◽  
Utility Functions ◽  
Linear Utility ◽  
Linear Utility Functions

AbstractThe reinsurer has a monopoly in the following sense: He will select a random variable P that determines the reinsurance premiums. The first insurer can purchase a payment of R (a random variable) for a premium of π = E[PR]. For known P, the first insurer chooses R to maximize his expected utility. Knowing this, i.e., the demand for reinsurance as a function of P, the reinsurer chooses P to maximize his utility. The resulting pair (P, R) is called the Bowley solution. Assuming exponential, quadratic and/or linear utility functions, some explicit results are obtained.

scholarly journals Agent negotiation on resources with nonlinear utility functions

2012 ◽  
Vol 9 (4) ◽  
pp. 1697-1720 ◽  
Author(s):  
Xiangrong Tong ◽  
Wei Zhang ◽  
Houkuan Huang
Keyword(s):  
Marginal Utility ◽  
Utility Functions ◽  
Prior Work ◽  
Negotiation Model ◽  
Agent Negotiation ◽  
Linear Utility ◽  
Diminishing Marginal Utility ◽  
Two Phases ◽  
The Relationship ◽  
Linear Utility Functions

To date, researches on agent multi-issue negotiation are mostly based on linear utility functions. However, the relationship between utilities and resources is usually saturated nonlinear. To this end, we expand linear utility functions to nonlinear cases according to the law of diminishing marginal utility. Furthermore, we propose a negotiation model on multiple divisible resources with two phases to realize Pareto optimal results. The computational complexity of the proposed algorithm is polynomial order. Experimental results show that the optimized efficiency of the proposed algorithm is distinctly higher than prior work.

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