Raymond R. Hill

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In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for(More)
We show how to find mixing probabilities, or weights, for composite probability mass functions (pmfs) for k-variate discrete random variables with specified marginal pmfs and a specified, feasible population correlation structure. We characterize a joint pmf that is a composition, or mixture, of 2k-1 extreme-correlation joint pmfs and the joint pmf under(More)
Combat, unlike many real-world processes, tends to be singular in nature. That is, there are not multiple occurrences from which to hypothesize a probability distribution model of the real-world system. Mission-level models may offer more flexibility on some measures due to their extended time frame. Additionally, the parameters involved in the(More)
We briefly describe genetic algorithms (GAs) and focus attention on initial population generation methods for two-dimensional knapsack problems. Based on work describing the probability a random solution vector is feasible for 0-1 knapsack problems, we propose a simple heuristic for randomly generating good initial populations for genetic algorithm(More)
This research develops an agent based simulation model for application to the sortie generation process, focusing on a single fighter aircraft unit. The simulation includes representations of each individual maintainer within the unit, along with supervisory agents that provide direction in the form of dynamic task prioritization and resource assignment.(More)