An unusual presentation of probable dementia: Rhyming,associations, and verbal disinhibition

We report a case of probable Alzheimer's disease who presented with the unusual feature of disinhibited rhyming. Core language skills were largely intact but generative language was characterized by semantic‐based associations, evident in tangential and associative content, and phonology‐based associations, evident in rhyming, in the context of prominent executive dysfunction. We suggest this pattern is underpinned by a failure to terminate or inhibit verbal associations resulting in a ‘loosening’ of associations at the level of conceptual preparation for spoken language.     

The Effects of Domain Knowledge and Instructional Manipulation on Creative Idea Generation

The experiment was designed to explore the effects of domain knowledge, instructional manipulation, and the interaction between them on creative idea generation. Three groups of participants who respectively possessed the domain knowledge of biology, sports, or neither were asked to finish two tasks: imagining an extraterrestrial animal and creating a new sport. Participants in each group were randomly assigned to one of three instructions, in order to encourage them to perform the tasks using a specific instance strategy (relying on specific instances), an abstract strategy (relying on abstract principles), or their habitual ways. Based on an analysis of the participants' verbal reports and their creations, the results suggested that domain knowledge enhanced the tendency to use the abstract strategy, and improved the originality and practicality of the generated ideas. Instructions also influenced the strategy participants used in creative idea generation. The instruction to use abstract principles brought forth the most original creations. Moreover, there was an interaction between domain knowledge and instructions. Encouraging participants to use the specific instance strategy blocked the knowledgeable people from developing novel ideas. Other factors, such as age, grade and gender, were found to be unrelated to either the originality or the practicality of the creations. The implications of the results were discussed in detail.     

Popper versus Wittgenstein on Truth, Necessity, and Scientific Hypotheses

Most philosophers of science maintain Confirmationism's central tenet, namely, that scientific theories are probabilistically confirmed by experimental successes. Against this dominant (and old) conception of experimental science, Popper's well-known, anti-inductivistic Falsificationism (’Deductivism’) has stood, virtually alone, since 1934. Indeed, it is Popper who tells us that it was he who killed Logical Positivism. It is also pretty well-known that Popper blames Wittgenstein for much that is wrong with Logical Positivism, just as he despises Wittgenstein and Wittgensteinian philosophers for abdicating philosophy's true mission. What is not well-known, however, especially because Popper neglected to tell us in 1934, is that Wittgenstein is very much an ally. It was Wittgenstein who rejected induction in the strongest possible terms as early as 1922, and it was Wittgenstein who similarly rejected Confirmationism approximately four years prior to Popper. The aims of this paper are to illuminate the substantial agreements between Popper and Wittgenstein and, by doing so, to clarify their important disagreement regarding the status of “strictly universal,” scientific theories (or hypotheses). This revised version was published online in August 2006 with corrections to the Cover Date.     

工会实践对员工工作幸福感的影响：基于工具-情感的双路径视角

日益僵化的传统管理手段、多元化的新生代员工利益诉求, 以及频发的企业劳资冲突, 导致中国基层工会在劳资关系中日趋式微, 进而陷入组织不愿投资、员工主动抛弃的双重困境。基于“工具-情感”双路径的视角和遵循“情境-认知”的逻辑框架, 为了在理论上和实证上回答“加强工会的实践效用能否给企业带来回报”这一问题, 拟通过在组织层次和个体层次测量工会实践的跨层次研究方法, 探讨工具性/情感性工会实践是否能够通过缓解劳资冲突提高员工工作幸福感这一理论问题, 并进一步研究在这一作用链上的边界条件。如此便揭示了基层工会在实现劳资双赢的实质性价值以及对员工幸福感的影响功效, 既是对管理科学“有良心研究”的伦理回应, 也是加强基层工会组织建设的重要策略。     

Co-PoeTryMe: Interactive poetry generation

PoeTryMe is a poetry generation system that autonomously produces poems from a set of initial parameters. After using it, creative writers and other users of this system expressed the desire to partake in the creative process by directly interacting with PoeTryMe. This paper is motivated by the previous impressions. It illustrates some of the challenges of automatic poetry generation, highlights limitations of PoeTryMe, and reports on recent efforts to address user feedback and provide alternative ways of using this system. First, making some functionalities available via a web API enabled their exploitation by other systems. Those include the generation of single lines as well as retrieval of related words, allowing for additional constraints on the number of syllables, sentiment and rhyme. On top of this API, a co-creative interface, Co-PoeTryMe, has been developed. Co-PoeTryMe allows users to either start from scratch or from a generated draft. Extensive editing functionality has been incorporated, in particular, allowing lines and words to be switched or replaced by newly generated alternatives. Co-PoeTryMe, its interface and the co-creative process for producing poetry are described, along with a user study that provided useful feedback. Users pointed out the strengths of this new system, including its capacities in providing inspiration, and giving the user the ability to customize an existing draft and visualize the changes, but also pointed out weaknesses, primarily by identifying potential improvements in the user interface.     

SOME THOUGHTS ABOUT THE REQUIREMENTS FOR REVIEWING BOOKS

Abstract: The quality of peer‐reviewed journals is vulnerable to the absence of declared standards for book reviews. Reviewers should agree to several simple rules before undertaking to review books and while writing them. Sensitivity to an author's aims is one requirement; familiarity with an author's previous and relevant publications is another. Critical judgment is always appropriate, but it can be set apart from an account of the ideas reviewed.     

Bayesian evaluation of informative hypotheses for multiple populations

The software package Bain can be used for the evaluation of informative hypotheses with respect to the parameters of a wide range of statistical models. For pairs of hypotheses the support in the data is quantified using the approximate adjusted fractional Bayes factor (BF). Currently, the data have to come from one population or have to consist of samples of equal size obtained from multiple populations. If samples of unequal size are obtained from multiple populations, the BF can be shown to be inconsistent. This paper examines how the approach implemented in Bain can be generalized such that multiple-population data can properly be processed. The resulting multiple-population approximate adjusted fractional Bayes factor is implemented in the R package Bain.     

Generation and evaluation of user tailored responses in multimodal dialogue

When people engage in conversation, they tailor their utterances to their conversational partners, whether these partners are other humans or computational systems. This tailoring, or adaptation to the partner takes place in all facets of human language use, and is based on a mental model or a user model of the conversational partner. Such adaptation has been shown to improve listeners’ comprehension, their satisfaction with an interactive system, the efficiency with which they execute conversational tasks, and the likelihood of achieving higher level goals such as changing the listener’s beliefs and attitudes. We focus on one aspect of adaptation, namely the tailoring of the content of dialogue system utterances for the higher level processes of persuasion, argumentation and advice-giving. Our hypothesis is that algorithms that adapt content for these processes, according to a user model, will improve the usability, efficiency, and effectiveness of dialogue systems. We describe a multimodal dialogue system and algorithms for adaptive content selection based on multi-attribute decision theory. We demonstrate experimentally the improved efficacy of system responses through the use of user models to both tailor the content of system utterances and to manipulate their conciseness.     

Where do hypotheses come from?

Why are human inferences sometimes remarkably close to the Bayesian ideal and other times systematically biased? In particular, why do humans make near-rational inferences in some natural domains where the candidate hypotheses are explicitly available, whereas tasks in similar domains requiring the self-generation of hypotheses produce systematic deviations from rational inference. We propose that these deviations arise from algorithmic processes approximating Bayes’ rule. Specifically in our account, hypotheses are generated stochastically from a sampling process, such that the sampled hypotheses form a Monte Carlo approximation of the posterior. While this approximation will converge to the true posterior in the limit of infinite samples, we take a small number of samples as we expect that the number of samples humans take is limited. We show that this model recreates several well-documented experimental findings such as anchoring and adjustment, subadditivity, superadditivity, the crowd within as well as the self-generation effect, the weak evidence, and the dud alternative effects. We confirm the model’s prediction that superadditivity and subadditivity can be induced within the same paradigm by manipulating the unpacking and typicality of hypotheses. We also partially confirm our model’s prediction about the effect of time pressure and cognitive load on these effects.