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原文連結
論文資訊
- 類型：已發表論文
- 日期：2010
摘要
Systems whose organization displays causal asymmetry constraints, from 演化ary trees to river basins or transport 網絡s, can often be described in terms of directed paths on a discrete set of arbitrary units including states in state spaces, feed-forward 神經 nets, the 演化ary history of a given collection of events or the chart of 計算 states visited along a complex computation. Such a set of paths defines a feed-forward, acyclic 網絡. A key problem associated with these systems involves characterizing their intrinsic degree of path reversibility: given an end node in the graph, what is the uncertainty of recovering the process backwards until the origin? Here, we propose a novel concept, topological reversibility, which is a measure of the complexity of the net that rigorously weights such uncertain
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