Conceptual dependency as the language of thought

Roger Schank's research in AI takes seriously the ideas that understanding natural language involves mapping its expressions into an internal representation scheme and that these internal representations have a syntax appropriate for computational operations. It therefore falls within the computational approach to the study of mind. This paper discusses certain aspects of Schank's approach in order to assess its potential adequacy as a (partial) model of cognition. This version of the Language of Thought hypothesis encounters some of the same difficulties that arise for Fodor's account.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43836/1/11229_2004_Article_BF00413665.pd

Special Issue "On Defining Artificial Intelligence"—Commentaries and Author's Response

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You Mate, I Mate: Macaque Females Synchronize Sex not Cycles

Extended female sexuality in species living in multimale-multifemale groups appears to enhance benefits from multiple males. Mating with many males, however, requires a low female monopolizability, which is affected by the spatiotemporal distribution of receptive females. Ovarian cycle synchrony potentially promotes overlapping receptivity if fertile and receptive periods are tightly linked. In primates, however, mating is often decoupled from hormonal control, hence reducing the need for synchronizing ovarian events. Here, we test the alternative hypothesis that females behaviorally coordinate their receptivity while simultaneously investigating ovarian cycle synchrony in wild, seasonal Assamese macaques (Macaca assamensis), a promiscuous species with extremely extended female sexuality. Using fecal hormone analysis to assess ovarian activity we show that fertile phases are randomly distributed, and that dyadic spatial proximity does not affect their distribution. We present evidence for mating synchrony, i.e., the occurrence of the females' receptivity was significantly associated with the proportion of other females mating on a given day. Our results suggest social facilitation of mating synchrony, which explains (i) the high number of simultaneously receptive females, and (ii) the low male mating skew in this species. Active mating synchronization may serve to enhance the benefits of extended female sexuality, and may proximately explain its patterning and maintenance

Construing the child reader: a cognitive stylistic analysis of the opening to Neil Gaiman’s The Graveyard Book

Neil Gaiman’s The Graveyard Book (2009) charts the story of Nobody Owens, a boy who is adopted by supernatural entities in the local graveyard after his family is murdered. This article draws on the notion of the “construed reader,” and combines two cognitive stylistic frameworks to analyse the opening section of the novel. In doing so, the article explores the representation and significance of the family home in relation to what follows in the narrative. The analysis largely draws on Text World Theory (Werth, 1999; Gavins, 2007), but also integrates some aspects of Cognitive Grammar (Langacker, 2008), which allows for a more nuanced discussion of textual features. The article pays particular attention to the way Gaiman frames his narrative and positions his reader to view the fictional events from a distinctive vantage point and subsequently demonstrates that a stylistic analysis of children’s literature can lay bare how such writing is designed with a young readership in mind

Goal-Based Scenarios

Schank argues that educational systems (for schools or business)should be redesigned so they consist of goal-based scenarios (GBS). The intent of a GBS is to provide motivation, a sense of accomplishment and a support system for the student, along with a focus on skills rather than facts. Goal-based scenarios allow students to pursue well-defined goals that they can recognize and understand. These goals must be of inherent interest to the student, and the skills needed to accomplish them must be used by the student in pursuit of the goal in question. The key is to embed instruction inside a student-developed need-to-know situation. When students want to know something to help them in a task they will be determined to learn what they need to know. Subjects such as cost accounting or geography should never be taught separately, but rather introduced within the context of a GBS to assist the student in successfully meeting the goals established by the scenario. Specific examples of GBSs for both schools and business training are provided

What We Learn When We Learn by Doing

Learning by doing is often talked about but rarely put into practice. It's easier for schools and businesses to fall back on the "drill them and test them" approch to education. This report discusses why learing by doing is the best educational approach because it capitalizes on people's natural learning mechanisms. Learning by doing builds a case base of functional skills and knowledge that are relevant to the learner

Where's the AI?

Four viewpoints about what artificial intelligence is about are surveyed. Schank describes a program exhibiting AI as one that can change as a result of interactions with the user. Such a program would have to process hundreds or thousands of examples as opposed to a handful. Because AI is a machine's attempt to explain the behavior of the (human) system it is trying to model, the ability of a program design to scale up is critical. Researchers need to face the complexities of scaling up to programs that actually serve a purpose. The move from toy domains into concrete ones has three big consequences for the development of AI. First, it will force software designers to face the idiosyncrasies of its users. Second, it will act as an important reality check between the language of the machine, the software, and the user. Third, the scaled-up preograms will become templates for future work

What to Know, How to Learn It

What should an educated person know? In school, little time is devoted to answering this question. The school already knows what you need to know: vocabulary about phyla, the plots of various pieces of last century's literature, and how to prove a theorem about triangles. When you try to get computers to know things in order to make them act "intelligently," however, it turns out that these are not at all the sorts of things they need to know. Computers need to know how to do things, how to comprehend what others have done and said, and how to learn from the mistakes it makes in doing all this