When and for whom do frequencies facilitate performance? On the role of numerical literacy

The thesis that the mind is better prepared to process frequencies—as compared to other numerical formats—continues to be debated. A recent aspect of this issue is the role of numeracy (numerical literacy; one's ability to understand and work with numerical information) and specifically the argument that individual differences in numeracy interact with numerical formats. This interaction, either that frequencies improve performance only for those of low numeracy or that frequencies work only for those of high numeracy, would suggest that better performance using frequencies could be due to (nonevolutionary) numeracy effects. The three present studies revisited prior work with cumulative probability, Bayesian reasoning, and scenario risk assessments to study the effects of numeracy on frequency facilitation. Results from these experiments consistently failed to replicate previous findings of interactions; however, a more consistent finding emerged of a straightforward frequency effect. The lack of interactions and observations of frequency main effects lend support to the evolutionary explanation of the frequency effect. In addition, some possible statistical processes are proposed to explain the observation of interactions in past studies.     

When intuitions are helpful: Prior beliefs can support reasoning in the bat-and-ball problem

Intuitions are often considered suboptimal because they can bias people's thinking. The bat-and-ball problem is a celebrated example of this potentially detrimental aspect of intuitions since it elicits a very appealing and prepotent intuitive but incorrect response. We propose to show that certain kinds of intuitions (i.e., prior beliefs) can help people to reason better on this task. In two experiments, participants answered either a classic congruent version of the bat-and-ball problem in which the intuitively cued response fitted with prior knowledge (i.e., was believable) or a modified incongruent version in which the intuitively cued response conflicted with prior knowledge (i.e., was unbelievable). Results indicate that participants who solved the modified unbelievable version performed better than participants who solved the classic believable version. Our data highlight that prior beliefs, even in the bat-and-ball problem, can accidentally make people perform better, probably because they encourage them to adopt a more effortful processing strategy.     

Technical intelligence in animals: the kea model

The ability to act on information flexibly is one of the cornerstones of intelligent behavior. As particularly informative example, tool-oriented behavior has been investigated to determine to which extent nonhuman animals understand means-end relations, object affordances, and have specific motor skills. Even planning with foresight, goal-directed problem solving and immediate causal inference have been a focus of research. However, these cognitive abilities may not be restricted to tool-using animals but may be found also in animals that show high levels of curiosity, object exploration and manipulation, and extractive foraging behavior. The kea, a New Zealand parrot, is a particularly good example. We here review findings from laboratory experiments and field observations of keas revealing surprising cognitive capacities in the physical domain. In an experiment with captive keas, the success rate of individuals that were allowed to observe a trained conspecific was significantly higher than that of naive control subjects due to their acquisition of some functional understanding of the task through observation. In a further experiment using the string-pulling task, a well-probed test for means-end comprehension, we found the keas finding an immediate solution that could not be improved upon in nine further trials. We interpreted their performance as insightful in the sense of being sensitive of the relevant functional properties of the task and thereby producing a new adaptive response without trial-and-error learning. Together, these findings contribute to the ongoing debate on the distribution of higher cognitive skills in the animal kingdom by showing high levels of sensorimotor intelligence in animals that do not use tools. In conclusion, we suggest that the 'Technical intelligence hypothesis' (Byrne, Machiavellian intelligence II: extensions and evaluations, pp 289-211, 1997), which has been proposed to explain the origin of the ape/monkey grade-shift in intelligence by a selection pressure upon an increased efficiency in foraging behavior, should be extended, that is, applied to some birds as well.     

Distant Causation in <Emphasis Type="Italic">C</Emphasis>+

The action language C+ of Giunchiglia, Lee, Lifschitz, McCain and Turner is a high-level, logical formalism for the representation of domains involving action and change. However, one cannot directly express relationships which hold between states more than one time-step distant, or even say that one action determines another at the next time. We present C+_timed, a generalization of C+ which removes these limitations. As for C+, translations to the language of causal theories are given. We also define a new kind of transition system called a ‘run system’ to provide a graphical semantics. Finally, we show how domains involving prohibition and permission can be modelled, by incorporating the ideas of another extension of C+.     

Representation and Reasoning about Evolutions of the World in the Context of Reasoning about Actions

The first step in reasoning about actions and change involves reasoning about how the world would evolve if a certain action is executed in a certain state. Most research on this assumes the evolution to be only a single step and focus on formulating the transition function that defines changes between states due to actions. In this paper we consider cases where the evolution is more than just a single change between one state and another. This is manifested when the execution of an action may trigger execution of other actions, or when multiple agents act on the environment following certain strategies.     

AI &; Law,Logic and Argument Schemes

This paper reviews the history of AI & Law research from the perspective of argument schemes. It starts with the observation that logic, although very well applicable to legal reasoning when there is uncertainty, vagueness and disagreement, is too abstract to give a fully satisfactory classification of legal argument types. It therefore needs to be supplemented with an argument-scheme approach, which classifies arguments not according to their logical form but according to their content, in particular, according to the roles that the various elements of an argument can play. This approach is then applied to legal reasoning, to identify some of the main legal argument schemes. It is also argued that much AI & Law research in fact employs the argument-scheme approach, although it usually is not presented as such. Finally, it is argued that the argument-scheme approach and the way it has been employed in AI & Law respects some of the main lessons to be learnt from Toulmin’s The Uses of Argument.     

Begging the Question in Arguments Based on Testimony

Summary This paper studies some classic cases of the fallacy of begging the question based on appeals to testimony containing circular reasoning. For example, suppose agents a, b and c vouch for d’s credentials, and agents b, d, and e vouch for a’s credentials. Such a sequence of reasoning is circular because a is offering testimony for d but d is offering testimony for a. The paper formulates and evaluates restrictions on the use of testimonial evidence that might be used to deal with such problematic arguments. One is called the Non-repeater Rule: in an extended sequence of argumentation based on testimony, once a source x has been appealed to at any given point in the sequence, that same source x must never be appealed to again at any next point in the same sequence.     

Distinguishing Between Causes and Enabling Conditions—Through Mental Models or Linguistic Cues?

The mental model theory of naive causal understanding and reasoning (Goldvarg & Johnson-Laird, 2001, Cognitive Science, 25, 565–610) claims that people distinguish between causes and enabling conditions on the basis of sets of models that represent possible causal situations. In the tasks used to test this hypothesis, however, the proposed set of models was confounded with linguistic cues that frame which event to assume as given (the enabling condition) and which to consider as responsible for the effect under this assumption (the cause). By disentangling these two factors, we were able to show that when identifying causes and enabling conditions in these tasks, people rely strongly on the linguistic cues but not on the proposed set of models and that this set of models does not even reflect people's typical interpretation of the tasks. We propose an alternative explanation that integrates syntactic and causal considerations.     

大学生亲社会倾向、亲社会推理以及它们的相关模式

采用《亲社会倾向测量》和《亲社会推理客观测量》研究了17至20岁大学生的六类亲社会倾向和亲社会推理的状况。发现大学生将利他的亲社会倾向列为六类倾向中的首位,接下来依次是紧急的、情绪性的、依从的、匿名的和公开的亲社会倾向;在亲社会推理五种类型中大学生选择比率最高的是内化价值定向的推理,接下来依次是刻板定向、需要定向和享乐主义定向的推理,所占比率最低的是赞扬定向的推理;六类亲社会倾向与亲社会推理之间具有特定的棚关模式．利他的和匿名的亲社会倾向与内化价值定向和刻板定向的推理正相关、与享乐主义定向及赞扬定向的推理负相关,公开的亲社会倾向与赞扬定向的推理正相关、与需要定向的推理负相关。跨文化比较证实,中美大学生的上述三个方面表现出一定的差异。     

Acquiring new spatial intuitions: learning to reason about rotations

There are certain simple rotations of objects that most people cannot reason about accurately. Reliable gaps in the understanding of a fundamental physical domain raise the question of how learning to reason in that domain might proceed. Using virtual reality techniques, this project investigated the nature of learning to reason across the domain of simple rotations. Learning consisted of the acquisition of spatial intuitions: there was encoding of useful spatiotemporal information in specific problem types and a gradual accumulation of this understanding across the domain. This pattern of learning through the accumulation of intuitions is especially interesting for rotational motion, in which an elegant domain-wide kinematics is available to support insightful learning. Individual ability to reason about rotations correlated highly with mastery motivation, skill in fluid reasoning, and skill in reasoning about spatial transformations. Thus, general cognitive advantages aided the understanding of individual rotations without guaranteeing immediate generalization across the domain.