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Empirical investigation of memory-based strategy on anomalous behaviorShota Matsubayashi, Kazuhisa Miwa (Nagoya University) , and Hitoshi Terai (Kindai University)We often encounter various anomalous behaviors of systems, such as machine failures, unexpected behaviors of intelligent agents, and irregular natural phenomena. In order to predict these anomalous behaviors, it is a useful strategy to infer the causal structure of target domains (the inference-based strategy). However, we assume another strategy, the memory-based strategy, to memorize the anomalous behaviors for the predictions. In the present study, we analyzed the features and benefits of the memory-based strategy using the spatial movement prediction task. Experiments 1 and 2 revealed that participants who were instructed to apply the memory-based strategy encoded only the anomalous instances, and not the regular instances. Additionally, the inference-based strategy was more effective for identifying the anomalous instances in a low-complexity task, whereas the memory-based strategy was more effective in a high-complexity task. Experiment 3 revealed that it was difficult to spontaneously select an appropriate strategy based on task complexity and to make benefits of the memory-based strategy for a high-complexity task even if the strategy was applied.

Objective The objective is to clarify the nature of cooperative moving behavior that realizes smooth traffic with others from the viewpoint of the trade-off between self-benefit and others’ benefit in the shared space. Background The shared space is not constrained by formal rules or behavioral norms, and is a potentially ambiguous situation where it is not clear who has priority. Therefore, the nature of cooperative behavior in the shared space is unclear. Method An experimental task was conducted to compare cooperative and nonurgent moving behavior regarding completion time (self-benefit), the amount of interruption (others’ benefit), and the amount of operation (cognitive effort). Results First, cooperative behavior benefits others. Second, although cooperative behavior decreases self-benefit compared to the baseline without any instructions, it can obtain relatively more self-benefit than nonurgent behavior without considering self-benefit. Third, cooperative behavior requires cognitive effort. Conclusion Cooperative behavior provides benefit to both oneself and others by spending cognitive effort in not interrupting others. Application If the nature of the cooperative behavior can be clarified, a cooperative module can be implemented into the algorithms of various mobilities.