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
我们正在建立一个决策理论,为了做到这一点,我们研究了鸟类是如何做决定的。在行为科学中,一个决定不被认为是深思熟虑的结果,而是指生物体在可能有几种行为时所做的事情。在人类中,内省可以产生一种感知(通常是不准确的),即自己的决定是由对每个选择的评估驱动的,因此人们通常认为动物也会通过评估选择来做出选择。如果这是真的,选择将花费信息处理的精力和时间:更多的选择,更多的时间。例如,如果狮子看到斑马,它可能会开始追逐,但如果它同时看到斑马和角马,它会评估它们的相对优点。如果它选择了斑马,它会花更长的时间开始追逐。例如,选择悖论指出,选择越多,选择就越困难。我们发现欧椋鸟的情况正好相反:它们在孤独的情况下做出选择比在有选择的情况下做出同样的选择要花更长的时间。在我们的实验中,单独面对每个选项所花费的时间非常准确地预测了从一个选择中取出它所花费的时间,而选择时间的缩短是模型工作方式的结果。此外,当单独满足每个选项时,接受每个选项的时间不仅取决于其绝对属性,还取决于它相对于上下文所带来的好处。为了处理所有这些发现,我们使用了源自生物学、经济学和心理学的思想,提出了顺序选择模型(简称SCM)。SCM假设鸟类在选择选项时使用的机制与它们单独面对每个选项时使用的机制相同。SCM包含了这样一种思想,即这些机制是随着环境的适应而进化的,在这种环境中,同时满足不同的选择是罕见的,但是依次满足它们是常见的。因此,对于同时进行的选择并没有特殊的适应性,但是与整个环境中的机会相比,追求每个选择的时间被精确地调整为利用它所带来的好处。SCM非常有效地解释和预测了我们最初实验中的结果(事后),但是理论模型的真正价值是当它适用于不同于导致其开始的情况时。我们建议在从未从这个角度研究过的选择问题中测试SCM,看看我们是否仍然观察到相同的预测精度,包括缩短选择中的决策时间。我们将使用需要认知的实验,这可能会很耗时。在其中一个实验中,蓝色光会持续0到30秒,之后会出现红色或绿色光(在单独的实验中)。如果它是红色的,鸟儿啄到钥匙后,等待15秒后得到食物,但如果它是绿色的,等待时间是30秒减去蓝色灯亮的时间。因此,如果蓝色的等待时间为10秒,那么绿色的等待时间为20秒,但如果蓝色的等待时间为25秒,那么绿色的等待时间为5秒。我们测量了椋鸟在红色和绿色无选择试验中啄食所需的时间。在另一个(选择)试验中,当蓝色的灯熄灭后,红色和绿色的灯同时出现,我们观察鸟儿选择了哪一个,花了多长时间。为了尽量减少等待食物的时间,如果蓝色食物持续时间少于15秒,鸟类应该选择红色食物,如果食物持续时间更长,鸟类应该选择绿色食物,但它们并不完全这样做。SCM通过在无选择试验中啄红色或绿色的时间来预测它们会做什么,它还预测了啄红色或绿色所需的时间:在有选择试验中,它应该比在无选择试验中花费更少的时间。因为选择涉及到在蓝色的持续时间内查阅记忆,所以人们可能会认为选择需要额外的时间,但SCM的预测正好相反。如果SCM预测得到满足,这将证明它适用于与它起源时非常不同的情况,因此它是一个非常有价值的模型。
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: