the weibull distribution has been widely used in survival and engineering reliability analysis. in life testing experiments is fairly common practice to terminate the experiment before all the items have failed, that means the data are censored. thus, the main objective of this paper is to estimate the reliability function of the weibull distribution with uncensored and censored data by using b...

Aiming at the limited energy characteristics of wireless sensor networks, we apply game theory to solve the power control problem to reduce energy consumption in wireless sensor networks. In this paper, a distributed power control algorithm based on non-cooperative game theory under incomplete information is proposed, which adopts Signal-to-Interference Noise Ratio (SINR) as utility function. T...

Bayesian decision-theory underpins robust decisionmaking in applications ranging from plant control to robotics where hedging action selection against state uncertainty is critical for minimizing low probability but potentially catastrophic outcomes (e.g, uncontrollable plant conditions or robots falling into stairwells). Unfortunately, belief state distributions in such settings are often comp...

In Bayesian approaches to utility learning from preferences, the objective is to infer a posterior belief distribution over an agent’s utility function based on previously observed agent preferences. From this, one can then estimate quantities such as the expected utility of a decision or the probability of an unobserved preference, which can then be used to make or suggest future decisions on ...

Traditional null hypothesis significance testing does not yield the probability of the null or its alternative and, therefore, cannot logically ground scientific decisions. The decision theory proposed here calculates the expected utility of an effect on the basis of (1) the probability of replicating it and (2) a utility function on its size. It takes significance tests--which place all value ...