Maximum Conditional Probability Stochastic Controller for Scalar Linear Systems with Additive Cauchy Noises

2018 ◽  
Author(s):  
Nati Twito ◽  
Moshe Idan ◽  
Jason L. Speyer
Keyword(s):  
Linear Systems ◽  
Conditional Probability ◽  
Stochastic Controller

ON THE CHECKING OF G-COHERENCE OF CONDITIONAL PROBABILITY BOUNDS

2003 ◽  
Vol 11 (supp02) ◽  
pp. 75-104 ◽  
Author(s):  
VERONICA BIAZZO ◽  
ANGELO GILIO ◽  
GIUSEPPE SANFILIPPO
Keyword(s):  
Linear Systems ◽  
Conditional Probability ◽  
Sufficient Conditions ◽  
Geometrical Approach ◽  
Additive Structure ◽  
Probability Bounds ◽  
Knowledge Based ◽  
Related Notion ◽  
Basic Set ◽  
Conditional Probability Bounds

We illustrate an approach to uncertain knowledge based on lower conditional probability bounds. We exploit the coherence principle of de Finetti and a related notion of generalized coherence (g-coherence), which is equivalent to the "avoiding uniform loss" property introduced by Walley for lower and upper probabilities. Based on the additive structure of random gains, we define suitable notions of non relevant gains and of basic sets of variables. Exploiting them, the linear systems in our algorithms can work with reduced sets of variables and/or constraints. In this paper, we illustrate the notions of non relevant gain and of basic set by examining several cases of imprecise assessments defined on families with three conditional events. We adopt a geometrical approach, obtaining some necessary and sufficient conditions for g-coherence. We also propose two algorithms which provide new strategies for reducing the number of constraints and for deciding g-coherence. In this way, we try to overcome the computational difficulties which arise when linear systems become intractable. Finally, we illustrate our methods by giving some examples.

scholarly journals Asynchronous Stochastic Controller Design for a Class of Markov Jump Linear Systems

2018 ◽  
Vol 12 (2) ◽  
pp. 41-51
Author(s):  
Mona Faraji-Niri ◽  
Mohammad Reza Jahed Motlagh ◽  
◽  
Keyword(s):  
Linear Systems ◽  
Controller Design ◽  
Markov Jump ◽  
Jump Linear Systems ◽  
Markov Jump Linear Systems ◽  
Stochastic Controller

Facial Likability and Smiling Enhance Cooperation, but Have No Direct Effect on Moralistic Punishment

2016 ◽  
Vol 63 (5) ◽  
pp. 263-277 ◽  
Author(s):  
Laura Mieth ◽  
Raoul Bell ◽  
Axel Buchner
Keyword(s):  
Conditional Probability ◽  
Direct Effect ◽  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Prisoner’S Dilemma Game ◽  
Costly Punishment ◽  
Prisoner's Dilemma Game ◽  
Moralistic Punishment

Abstract. The present study serves to test how positive and negative appearance-based expectations affect cooperation and punishment. Participants played a prisoner’s dilemma game with partners who either cooperated or defected. Then they were given a costly punishment option: They could spend money to decrease the payoffs of their partners. Aggregated over trials, participants spent more money for punishing the defection of likable-looking and smiling partners compared to punishing the defection of unlikable-looking and nonsmiling partners, but only because participants were more likely to cooperate with likable-looking and smiling partners, which provided the participants with more opportunities for moralistic punishment. When expressed as a conditional probability, moralistic punishment did not differ as a function of the partners’ facial likability. Smiling had no effect on the probability of moralistic punishment, but punishment was milder for smiling in comparison to nonsmiling partners.

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