Morell, V. (2007). Nicola Clayton profile. Nicky and the jays (Vol. 315).
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Pennisi, E. (2006). Animal cognition. Man's best friend(s) reveal the possible roots of social intelligence (Vol. 312).
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Pennisi, E. (2006). Animal cognition. Social animals prove their smarts (Vol. 312).
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Subiaul, F., Cantlon, J. F., Holloway, R. L., & Terrace, H. S. (2004). Cognitive imitation in rhesus macaques. Science, 305(5682), 407–410.
Abstract: Experiments on imitation typically evaluate a student's ability to copy some feature of an expert's motor behavior. Here, we describe a type of observational learning in which a student copies a cognitive rule rather than a specific motor action. Two rhesus macaques were trained to respond, in a prescribed order, to different sets of photographs that were displayed on a touch-sensitive monitor. Because the position of the photographs varied randomly from trial to trial, sequences could not be learned by motor imitation. Both monkeys learned new sequences more rapidly after observing an expert execute those sequences than when they had to learn new sequences entirely by trial and error.
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Weir, A. A. S., Chappell, J., & Kacelnik, A. (2002). Shaping of hooks in New Caledonian crows. Science, 297(5583), 981.
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Williams, N. (1997). Evolutionary psychologists look for roots of cognition (Vol. 275).
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Real, L. A. (1991). Animal choice behavior and the evolution of cognitive architecture. Science, 253(5023), 980–986.
Abstract: Animals process sensory information according to specific computational rules and, subsequently, form representations of their environments that form the basis for decisions and choices. The specific computational rules used by organisms will often be evolutionarily adaptive by generating higher probabilities of survival, reproduction, and resource acquisition. Experiments with enclosed colonies of bumblebees constrained to foraging on artificial flowers suggest that the bumblebee's cognitive architecture is designed to efficiently exploit floral resources from spatially structured environments given limits on memory and the neuronal processing of information. A non-linear relationship between the biomechanics of nectar extraction and rates of net energetic gain by individual bees may account for sensitivities to both the arithmetic mean and variance in reward distributions in flowers. Heuristic rules that lead to efficient resource exploitation may also lead to subjective misperception of likelihoods. Subjective probability formation may then be viewed as a problem in pattern recognition subject to specific sampling schemes and memory constraints.
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Straub, A. (2007). An intelligent crow beats a lab. Science, 316(5825), 688.
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Zentall, T. R. (2002). A cognitive behaviorist approach to the study of animal behavior. J Gen Psychol, 129(4), 328–363.
Abstract: Traditional psychological approaches to animal learning and behavior have involved either the atheoretical behaviorist approach proposed by B. F. Skinner (1938), in which input-output relations are described in response to environmental manipulations, or the theoretical behaviorist approach offered by C. L Hull (1943), in which associations mediated by several hypothetical constructs and intervening variables are formed between stimuli and responses. Recently, the application of a cognitive behaviorist approach to animal learning and behavior has been found to have considerable value as a research tool. This perspective has grown out of E. C. Tolman's cognitive approach to learning in which behavior is mediated by mechanisms that are not directly observable but can be inferred from the results of critical experiments. In the present article, the author presents several examples of the successful application of the cognitive behaviorist approach. In each case, the experiments have been designed to distinguish between more traditional mechanisms and those mediated by hypothesized internal representations. These examples were selected because the evidence suggests that some form of active cognitive organization is needed to account for the behavioral results.
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Kirkwood, J. K. (2000). Animal minds and animal welfare. Vet. Rec., 146(11), 327.
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