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Dyer, F. C. (1998). Spatial Cognition: Lessons from Central-place Foraging Insects. In Russell P. Balda, Irene M. Pepperberg, & Alan C. Kamil (Eds.), Animal Cognition in Nature (pp. 119–154). London: Academic Press.
Abstract: Summary Spatial orientation has played an extremely important role in the development of ideas about the behavioral capacities of animals. Indeed, as the modern scientific study of animal behavior emerged from its roots in zoology and experimental psychology, studies of spatial orientation figured in the work of many of the pioneering researchers, including Tinbergen (), von ), Watson () and .
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Smith, W. J. (1998). Cognitive Implications of an Information-sharing Model of Animal Communication. In Russell P. Balda, Irene M. Pepperberg, & Alan C. Kamil (Eds.), Animal Cognition in Nature (pp. 227–243). London: Academic Press.
Abstract: Summary In social communication, one animal signals and another responds. Several cognitive steps are involved as the second animal selects its responses; these steps can be described as follows in terms of an informational model. First, the responding individual must evaluate the information made available by the signaling on the basis of other information, available from sources contextual to the signal. Second, the respondent must fit all of the relevant information into patterns generated from recall of past events (conscious recall is not generally required; pattern fitting is a fundamental skill). Third, conditional predictions must be made; and fourth, the individual must test and modify any of these predictions for which significant consequences exist. Many vertebrate animals appear to respond to signaling with considerable flexibility. Communicative events are thus complex but are by no means intractable. Indeed, communication provides us with excellent opportunities to investigate animal cognition.
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Beer, C. G. (1998). Varying Views of Animal and Human Cognition. In Russell P. Balda, Irene M. Pepperberg, & Alan C. Kamil (Eds.), Animal Cognition in Nature (pp. 435–456). London: Academic Press.
Abstract: Summary In this chapter I want to stand back from the splendid empirical work on animal cognitive capacities that is the focus of this book, and look at the broader context of cognitive concerns within which the work can be viewed. Indeed even the term `cognitive ethology' currently connotes and denotes more than is represented here, as other collections of articles, such as and , exemplify. I include the current descendants of behavioristic learning theory, evolutionary epistemology, evolutionary psychology and the recent comparative turn that has been taken in cognitive science. These several approaches, despite their considerable overlap, often appear independent and even ignorant of one another. Like the proverbial blind men feeling the hide of an elephant, they touch hands from time to time, yet collectively have only a piecemeal and distributed understanding of the shape of the whole. Although each approach may indeed need the space to work out its own conceptual and methodological preoccupations without confounding interference from other views, a utopian spirit envisages an ultimate coming together, a more comprehensive realization of the synthetic approach to animal cognition that is this book's theme.
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Baron-Cohen S, Leslie AM, & Frith U. (1985). Does the autistic child have a “theory of mind”? Cognition, 21, 37.
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Wimmer H, & Perner J. (1983). Beliefs about beliefs: representation and constraining function of wrong beliefs in young children's understanding of deception. Cognition, 13, 103.
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Hauser MD. (1997). Artifactual kinds and functional design features: what a primate understands without language. Cognition, 64, 285.
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Premack D, & Premack AJ. (1994). Levels of causal understanding in chimpanzees and children. Cognition, 50, 347.
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Santos LR, Hauser MD, & Spelke ES. (2001). Recognition and categorization of biologically significant objects by rhesus monkeys (Macaca mulatta): the domain of food. Cognition, 82, 127.
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Lieberman, D. (1993).
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BRYSON, J. O. A. N. N. A. J. EVIDENCE OF MODULARITY FROM PRIMATE ERRORS DURING TASK LEARNING. Retrieved May 15, 2024, from http://dx.doi.org/10.1142/9789812701886_0031
Abstract: The last two decades have seen a great deal of theorising and speculation about
the modular nature of human intelligence, as well as a rise in use of modular
architectures in artificial intelligence. Nevertheless, whether such models of natural
intelligence are well supported is still an issue of debate. In this paper, I propose
that the most important criteria for modularity is specialised representations. I
present a modular model of primate learning of the transitive inference task, and
propose an extension to this model which would explain task-learning results in
other domains. I also briefly relate this work to both neuroscience and established
AI learning architectures.
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