The Effect of Knowledge Accumulation on Support for Workplace Accommodation

We investigated the relationship between knowledge about the demonstrated benefits of breastfeeding and individual support for breastfeeding accommodation in the workplace. We tested our hypotheses by asking participants to respond to vignettes that described the factors a Director of Human Resources had to consider in responding to the needs of a breastfeeding employee. We found that participants had a low level of knowledge about the benefits of breastfeeding for child, mother, and organization. Participants with children reported stronger support for accommodation, and the level of knowledge about the benefits of breastfeeding mediated this effect. The results showed that participants in executive level positions, and who had no children, were the least supportive of accommodation. There were no occupational differences in responses to the support measure.     

A formalisation of violation, error recovery, and enforcement in the bit transmission problem

The design of complex multi-agent systems is increasingly having to confront the possibility that agents may not behave as they are supposed to. In addition to analysing the properties that hold if protocols are followed correctly, it is also necessary to predict, test, and verify the properties that would hold if these protocols were to be violated. We illustrate how the formal machinery of deontic interpreted systems can be applied to the analysis of such problems by considering three variations of the bit transmission problem. The first, an example in which an agent may fail to do something it is supposed to do, shows how we deal with violations of protocols and specifications generally. The second, an example in which an agent may do something it is not supposed to do, shows how it is possible to specify and analyse remedial or error-recovery procedures. The third combines both kinds of faults and introduces a new component into the system, a controller, whose role is to enforce compliance with the protocol. In each case the formal analysis is used to test whether critical properties of the system are compromised, in this example, the reliable communication of information from one agent to the other.     

Modeling ratings of in-vehicle alerts to pedestrian by leveraging field operational tests data in a controlled laboratory study

We show how to leverage expensive field operational tests (FOT) data in a controlled laboratory study when defining an in-vehicle algorithm that alerts drivers to pedestrians. We used an empirical approach that quantifies the relative level with which drivers are likely to accept alerts to pedestrians. The approach was used in two studies to investigate a range of contextual factors known to influence driver ratings of alerts to pedestrians issued by a driver-assistance system. Regression analysis shows that four factors consisting of combinations of pedestrian location and motion relative to the road ahead of the vehicle explain 85% of the variability in drivers’ ratings of alerts. Adding two factors related to the uncertainty of the pedestrians’ future path improves the model slightly. These findings suggest that drivers’ assessment of the danger associated with pedestrians derives largely from the possibility that they might move into the vehicle’s path, even when the vehicle is not on a collision course with the pedestrians. The less probable such an event seems, the less accepted an alert will be. Time to arrival (TTA) improved the regression model only when restricted to pedestrians in clear need of an alert, but was also found to have an effect in alert timing. This finding suggests that four contextual factors largely define the perceptual cues that drivers use to rate alerts to pedestrians.     

Young children’s developing conception of knowledge and ignorance: work in progress

When do children acquire an understanding of knowledge and ignorance? We analyzed the early development of children’s spontaneous references to knowing and not knowing and conclude that 2-year-olds talk explicitly and cogently about their own knowledge as well as that of an interlocutor. Two-year-olds also admit their own ignorance. Moreover, consistent with their realization that an informant may know what they do not, 2-year-olds ask many information-seeking questions. Finally, we discuss children’s receptivity and skepticism, especially toward the counterintuitive claims of an adult. We conclude that children’s conception of knowledge and ignorance begins early but undergoes protracted refinement.     

Bayes and blickets: effects of knowledge on causal induction in children and adults

People are adept at inferring novel causal relations, even from only a few observations. Prior knowledge about the probability of encountering causal relations of various types and the nature of the mechanisms relating causes and effects plays a crucial role in these inferences. We test a formal account of how this knowledge can be used and acquired, based on analyzing causal induction as Bayesian inference. Five studies explored the predictions of this account with adults and 4-year-olds, using tasks in which participants learned about the causal properties of a set of objects. The studies varied the two factors that our Bayesian approach predicted should be relevant to causal induction: the prior probability with which causal relations exist, and the assumption of a deterministic or a probabilistic relation between cause and effect. Adults' judgments (Experiments 1, 2, and 4) were in close correspondence with the quantitative predictions of the model, and children's judgments (Experiments 3 and 5) agreed qualitatively with this account.     

Estimation of careless error and lucky guess probabilities for dichotomous test items: A psychometric application of a biometric latent class model with random effects

Medical research has extensively dealt with the estimation of the accuracy (sensitivity and specificity) of a diagnostic test for screening individuals. In this paper we apply the biometric latent class model with random effects by Qu, Tan, and Kutner [(1996). Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. Biometrics, 52, 797-810] to estimate the response error (careless error and lucky guess) probabilities for dichotomous test items in the psychometric theory of knowledge spaces. The approach is illustrated with simulated data. In particular, we extend this approach to give a generalization of the basic local independence model in knowledge space theory. This allows for local dependence among the indicators given the knowledge state of an examinee and/or for the incorporation of covariates.     

归纳接受与知识

归纳推理的结论进入知识集合的时候有一个“跳跃”的过程。根据什么规则接受归纳结论是归纳逻辑研究中的一个重要问题。概率接受规则与知识集合应当满足的一致性条件和演绎封闭条件之间存在着不协调,这种不协调性导致了抽彩悖论。该文介绍有代表性的归纳接受理论,指出归纳接受问题对归纳逻辑发展的影响。     

Automatic knowledge learning and case adaptation with a hybrid committee approach

When Case Based Reasoning systems are applied to real-world problems, the retrieved solutions usually require adaptations in order to be used on new contexts. Therefore, case adaptation is a desirable capability. However, case adaptation is still a challenge for this research area. In general, the acquisition of knowledge for case adaptation is harder than the acquisition of cases. This paper explores the automatic learning of adaptation knowledge and explores the use of a hybrid committee approach for automatic case adaptation.     

Beyond subgoaling: A dynamic knowledge generation framework for creative problem solving in cognitive architectures

In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures.     

Knowledge, expectations, and inductive reasoning within conceptual hierarchies

Previous research (e.g. Cognition 64 (1997) 73) suggests that the privileged level for inductive inference in a folk biological conceptual hierarchy does not correspond to the “basic” level (i.e. the level at which concepts are both informative and distinct). To further explore inductive inference within conceptual hierarchies, we examine relations between knowledge of concepts at different hierarchical levels, expectations about conceptual coherence, and inductive inference. In Experiments 1 and 2, 5- and 8-year-olds and adults listed features of living kind (Experiments 1 and 2) and artifact (Experiment 2) concepts at different hierarchical levels (e.g. plant, tree, oak, desert oak), and also rated the strength of generalizations to the same concepts. For living kinds, the level that showed a relative advantage on these two tasks differed; the greatest increase in features listed tended to occur at the life-form level (e.g. tree), whereas the greatest increase in inductive strength tended to occur at the folk-generic level (e.g. oak). Knowledge and induction also showed different developmental trajectories. For artifact concepts, the levels at which the greatest gains in knowledge and induction occurred were more varied, and corresponded more closely across tasks. In Experiment 3, adults reported beliefs about within-category similarity for concepts at different levels of animal, plant and artifact hierarchies, and rated inductive strength as before. For living kind concepts, expectations about category coherence predicted patterns of inductions; knowledge did not. For artifact concepts, both knowledge and expectations predicted patterns of induction. Results suggest that beliefs about conceptual coherence play an important role in guiding inductive inference, that this role may be largely independent of specific knowledge of concepts, and that such beliefs are especially important in reasoning about living kinds.