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Assessing and Enhancing the Welfare of Animals with Equivocal and Reliable Cues

Abstract

The actions of human caretakers strongly influence animals living under human care. Here, we consider how intentional and unintentional signals provided by caretakers can inform our assessment of animals' well-being as well as help to support it. Our aim is to assist in further developing techniques to learn animals' affective state from their behavior and to provide simple suggestions for how animal caretakers' behavior can support animal welfare. We suggest that anticipatory behavior towards expected rewards is related to decision-making behavior as viewed through the cognitive bias lens. By considering the predictions of the theories associated with anticipatory behavior and cognitive bias, we propose to use specific cues to probe the cumulative affective state of animals. Additionally, our commentary draws on the logic of reward sensitivity and judgement bias theories to develop a framework that suggests how reliable and equivocal signals may influence animals' affective states. Application of this framework may be useful in supporting the welfare of animals in human care.

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