Spatial Information Theory - 12th International Conference, COSIT 2015, Santa Fe, NM, USA, October 12-16, 2015, Proceedings
Spatial Information Theory - 12th International Conference, COSIT 2015, Santa Fe, NM, USA, October 12-16, 2015, Proceedings
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空间信息理论 - 第 12 届国际会议，COSIT 2015，美国新墨西哥州圣达菲，2015 年 10 月 12-16 日，论文集
DOI：
10.1007/978-3-319-23374-1_2
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Galton A
中科院分区：
文献类型：
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作者：
Galton A
本文关注检测时空数据中的因果关系的问题。与之前大多数关于因果关系的工作相比，我们采用逻辑方法而不是概率方法。通过定义所需因果规则的逻辑形式，本文开发的算法搜索该形式的规则实例，以尽可能全面地解释数据集中发现的观察结果。对合成数据的实验表明，在已知潜在因果规则的情况下，该算法能够检索生成数据的规则的近似值。然而，有关澳大利亚大型河流系统中鱼类运动的真实数据的实验揭示了显着的实际局限性，这主要是由于此类运动数据的粗粒度造成的。作为回应，进一步的实验没有关注严格的因果关系（环境事件引发运动事件），而是关注永久化（环境条件是持续运动过程的驱动因素）。在重新分配任务以搜索与永久兼容的规则的不同逻辑形式之后，我们的算法能够识别解释大部分鱼类运动的永久规则。例如，仅考虑水位变化的情况下，在六年期间检测到的鱼类远距离移动中，约有五分之一是由 26 条规则解释的。
This paper is concerned with the problem of detecting causality in spatiotemporal data. In contrast to most previous work on causality, we adopt a logical rather than a probabilistic approach. By defining the logical form of the desired causal rules, the algorithm developed in this paper searches for instances of rules of that form that explain as fully as possible the observations found in a data set. Experiments with synthetic data, where the underlying causal rules are known, show that in many cases the algorithm is able to retrieve close approximations to the rules that generated the data. However, experiments with real data concerning the movement of fish in a large Australian river system reveal significant practical limitations, primarily as a consequence of the coarse granularity of such movement data. In response, instead of focusing on strict causation (where an environmental event initiates a movement event), further experiments focused on perpetuation (where environmental conditions are the drivers of ongoing processes of movement). After retasking to search for a different logical form of rules compatible with perpetuation, our algorithm was able to identify perpetuation rules that explain a significant proportion of the fish movements. For example, approximately one fifth of the detected long-range movements of fish over a period of six years were accounted for by 26 rules taking account of variations in water-level alone.