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Bayesian networks provide an elegant formalism to perform inferences under uncertainty. Their shortcoming of being propositional in nature, however, restricts their expressive power and restrains their use in domains where number of instances may vary from situation to situation. First-order Logic (FOL), on the other hand, enjoys that power of expressiveness but is deterministic in nature. Integration...
The paper applies particle swarm optimization (PSO) technique to identify effective courses of action (COAs) in a dynamic uncertain situation. The uncertain situation is modeled using timed influence nets (TINs), an instance of Dynamic Bayesian Networks. The TIN-based framework aids a system analyst in connecting a set of actionable events and a set of desired effects through chains of cause and effect...
An evolutionary algorithm-based approach to identify effective courses of action (COAs) in dynamic uncertain situations is presented. The uncertain situation is modeled using timed influence nets, an instance of dynamic Bayesian networks. The approach makes significant enhancements to the current trial-and-error-based manual technique, which is not only labor intensive but also not capable of modeling...
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