Irrelevance in uncertain temporal reasoning

In the presence of uncertainty, relevance of information degenerates as time evolves. The work shows that this degeneration occurs in probabilistic temporal reasoning. A mechanism for analyzing this phenomenon uses a Markov chain representation and a degree of relevance measure called temporal extraneousness. Efficiency of probabilistic temporal reasoning can be improved by ignoring irrelevant and weakly relevant information. The analysis allows one to identify the portion of event history affecting the time instant of interest. The duration of relevant history depends on the dynamic nature of the system and the chosen relevance threshold. These notions are used to prune time-sliced Bayesian networks which constitute a popular probabilistic temporal reasoning knowledge representation