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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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Kirkwood, J. K. (2000). Animal minds and animal welfare. Vet. Rec., 146(11), 327.
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Reznikova, Z. I. (2006). [The study of tool use as the way for general estimation of cognitive abilities in animals]. Zh Obshch Biol, 67(1), 3–22.
Abstract: Investigation of tool use is an effective way to determine cognitive abilities of animals. This approach raises hypotheses, which delineate limits of animal's competence in understanding of objects properties and interrelations and the influence of individual and social experience on their behaviour. On the basis of brief review of different models of manipulation with objects and tools manufacturing (detaching, subtracting and reshaping) by various animals (from elephants to ants) in natural conditions the experimental data concerning tool usage was considered. Tool behaviour of anumals could be observed rarely and its distribution among different taxons is rather odd. Recent studies have revealed that some species (for instance, bonobos and tamarins) which didn't manipulate tools in wild life appears to be an advanced tool users and even manufacturers in laboratory. Experimental studies of animals tool use include investigation of their ability to use objects physical properties, to categorize objects involved in tool activity by its functional properties, to take forces affecting objects into account, as well as their capacity of planning their actions. The crucial question is whether animals can abstract general principles of relations between objects regardless of the exact circumstances, or they develop specific associations between concerete things and situations. Effectiveness of laboratory methods is estimated in the review basing on comparative studies of tool behaviour, such as “support problem”, “stick problem”, “tube- and tube-trap problem”, and “reserve tube problem”. Levels of social learning, the role of imprinting, and species-specific predisposition to formation of specific domains are discussed. Experimental investigation of tool use allows estimation of the individuals' intelligence in populations. A hypothesis suggesting that strong predisposition to formation of specific associations can serve as a driving force and at the same time as obstacle to animals' activity is discussed. In several “technically gifted” species (such as woodpecker finches, New Caledonian crows, and chimpanzees) tool use seems to be guided by a rapid process of trial and error learning. Individuals that are predisposed to learn specific connections do this too quickly and thus become enslaved by stereotypic solutions of raising problems.
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Straub, A. (2007). An intelligent crow beats a lab. Science, 316(5825), 688.
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