We develop a framework based on Bayesian model averaging to explain how animals cope with uncertainty about contingencies in classical conditioning experiments. Traditional accounts of conditioning fit parameters within a fixed generative model of reinforcer delivery; uncertainty over the model structure is not considered. We apply the theory to explain the puzzling relationship between second-...

Dependent Variable: Y Method: Least Squares Date: 05/23/00 Time: 05:55 Sample: 1 33 Included observations: 33 Variable Coefficient Std. Error t-Statistic Prob. C 102192.4 12799.83 7.983891 0.0000 N -9074.674 2052.674 -4.420904 0.0001 P 0.354668 0.072681 4.879810 0.0000 I 1.287923 0.543294 2.370584 0.0246 R-squared 0.618154 Mean dependent var 125634.6 Adjusted R-squared 0.578653 S.D. dependent v...

This chapter of a collective book aims at presenting the basics of decision making under risk. We ...rst de...ne notions of risk and increasing risk and recall de...nitions and classi...cations (that are valid independently of any representation) of behavior under risk. We then review the classical model of expected utility due to von Neumann and Morgenstern and its main properties. Issues rais...

We begin with some thoughts on how model theory relates to other parts of mathematics, and on the indirect role of Gödel’s incompleteness theorem in this connection. With this in mind we consider in Section 2 the fields of real and p-adic numbers and show how these algebraic objects are understood model-theoretically: theorems of Tarski, Kochen, and Macintyre. This leads naturally to a discussi...

Robert J. Barro’s article, “Inflation and Growth,” presents the results of regressions of per capita output growth on inflation across countries and over time. He finds that there is a statistically significant negative slope coefficient estimate in these regressions; the estimate usually lies between 0.02 and 0.04. As far as I can tell, Barro wants to interpret these results as follows. Suppos...

in any classical risk model one of the important random variable is time to ruin. as time to ruin warns the management for possible adverse situations that may arise, the distribution of time to ruin place a vital role in the day to day transactions of the any insurance company. moments of the distribution are also important as coefficient of skewness of the distribution is very important in ac...

in many real world assembly line systems which the work-piece is of large size more than one worker work on the same work-piece in each station. this type of assembly line is called multi-manned assembly line (mal). in the classical multi-manned assembly line balancing problem (malbp) the objective is to minimize the manpower needed to manufacture one product unit. apart from the manpower, othe...

Introduction: Researchers have employed surface electromyography (EMG) to study the human masticatory system and the relationship between the activity of masticatory muscles and the mechanical features of mastication. This relationship has several applications in food texture analysis, control of prosthetic limbs, rehabilitation, and teleoperated robots. Materials and Methods: In this paper, w...

In this paper, using high order perturbative series expansion method, the critical exponents of the order parameter and susceptibility in transition from ferromagnetic to disordered phases for 1D quantum Ising model in transverse field, with ferromagnetic nearest neighbor and anti-ferromagnetic next to nearest neighbor interactions, are calculated. It is found that for small value of the frustr...