organizational performance--are inevitable. Our computational experiments show that delays increase learning complexity and … performance heterogeneity through two mechanisms. First, complexity of state-space and, therefore, of learning grows exponentially … overcoming temporal complexity and the impact of initial cognitive maps are discussed. …

global warming policies. Because there are typically profound uncertainties in these models, a simulation approach is often …

portfolios of credit-sensitive assets such as loans and corporate bonds. Monte Carlo simulation is an important tool for … performing computations in these models. This paper develops, analyzes, and evaluates two simulation algorithms for intensity … Zeevi, stochastic models and simulation.</i> …

Sequential sampling problems arise in stochastic simulation and many other applications. Sampling is used to infer the …, as is common in the literature. <i>This paper was accepted by Assaf Zeevi, stochastic models and simulation.</i> …

simulation experiment. We also show how different definitions of the sample space yield different variants of the LR method, some …

the problem of using simulation to estimate the number of transitions it takes the process to enter \scr{A}. Using …

In a discrete-event simulation, the information related to the events scheduled to occur in the future is kept in a …

approach to simulate comparative solutions for specific contracts under different parametric settings. Through a simulation …

sources of uncertainty as catch per species, catch per unit of effort, weather, and markets by a computer simulation procedure …