Animal Decision-Making: Sequential Versus Simultaneous Choice
Animal Decision-Making: Sequential Versus Simultaneous Choice
批准号:
BB/G007144/1
负责人:
Alex Kacelnik
金额:
$60.93万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2009
资助国家:
英国
项目状态:
已结题
起止时间:
2009 至 --
中文摘要
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英文摘要
We are building a theory of decision-making, and to do this we investigate how birds take decisions. In behavioural science a decision is not assumed to result from thoughtful deliberation but refers to what organisms do when several actions are possible. In humans, introspection can create the perception (often inaccurate) that one's own decisions are driven by evaluation of each alternative, and as a consequence people often assume that animals also choose by evaluating alternatives. If this were true, choosing would take information-processing effort and time: more options, more time. For instance, if a lion sees a zebra, it may start a chase, but if it sees both a zebra and a wildebeest, it would evaluate their relative merits. If it chooses the zebra, it would have taken longer to start the chase. The paradox of choice, for instance, states that more options make choice more difficult. We found that the opposite is true in starlings: they take longer to take a lonely alternative than when they take the same alternative in a choice situation. In our experiments the times taken to take each option when faced alone predict very accurately how long it takes when it takes it out of a choice, and the shortening of time in choices results from the way the model works. Further, the time to accept each option when it is met alone depends not only on its absolute properties, but also on the benefit it gives relative to the context. To deal with all these findings, we used ideas originating in biology, economics and psychology to propose the Sequential Choice Model or SCM for short. SCM postulates that the mechanisms used by birds to choose between options are the same they use when facing each option alone. SCM incorporates the idea that these mechanisms evolved as adaptations to environments in which meeting different options simultaneously is rare, but meeting them sequentially is common. Thus, there are no special adaptations for simultaneous choices, but the time to chase each alternative is precisely tuned to exploit the benefits it gives compared with the opportunities in the whole environment. The SCM very effectively explained and predicted (post-hoc) the results in our original experiments, but the real value of a theoretical model is when it works for situations different from those that led to its inception. We propose to test SCM in choice problems that have never been studied from this perspective and to see if we still observe the same predictive precision including the shortening of decision times in choices. We'll use experiments that require cognition that might be expected to be time consuming. In one of them, a blue light is shown for a time lasting between 0 and 30 s, and after that either a red or a green light shows (In separate trials). If it is red, after the bird pecks the key it gets food after waiting 15 s, but if it is green the waiting time is 30 s minus the time the blue light had been on. Thus, if blue lasted 10 s, then green's waiting is 20 s, but if blue lasted 25 s, then green's waiting is 5 s. We measure how long the starling takes to peck in both red and green no-choice trials. On other (choice) trials, after the blue light goes off both red and green show, and we look at which one the bird chooses and how long it takes. To minimise waiting for food, birds should choose red if blue lasted less than 15 s and green if it lasted longer, but they don't do exactly this. SCM predicts what they will do using the times to peck red or green in no-choice trials, and it also predicts how long it will take to peck either: it should take less in choice than in no-choice trials. Since choice involves consulting the memory for the duration of blue one might expect choice to take extra time, but SCM predicts the opposite. If the SCM predictions are met, this would be evidence that it applies to very different situations from those in which it originated, and hence that it is a very valuable model.
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DOI:
--
发表时间:
2012
期刊:
影响因子:
--
作者:
[Kacelnik A]
通讯作者:
Kacelnik A
DOI:
10.1016/j.beproc.2011.09.007
发表时间:
2012-02-01
期刊:
BEHAVIOURAL PROCESSES
影响因子:
1.3
作者:
[Aw, Justine, Monteiro, Tiago, Kacelnik, Alex]
通讯作者:
Kacelnik, Alex
Choosing fast and simply: Construction of preferences by starlings through parallel option valuation.
快速而简单的选择:椋鸟通过平行期权估值构建偏好。
DOI:
10.1371/journal.pbio.3000841
发表时间:
2020
期刊:
PLoS biology
影响因子:
9.8
作者:
[Monteiro T]
通讯作者:
Monteiro T
DOI:
--
发表时间:
2011
期刊:
影响因子:
--
作者:
[Kacelnik A]
通讯作者:
Kacelnik A
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: