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Dyer, F. C. (2002). Animal behaviour: when it pays to waggle (Vol. 419).
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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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Gould, J. L. (2004). Animal cognition. Curr Biol, 14(10), R372–5.
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Epstein, R. (1985). Animal cognition as the praxist views it. Neurosci Biobehav Rev, 9(4), 623–630.
Abstract: The distinction between psychology and praxics provides a clear answer to the question of animal cognition. As Griffin and others have noted, the kinds of behavioral phenomena that lead psychologists to speak of cognition in humans are also observed in nonhuman animals, and therefore those who are convinced of the legitimacy of psychology should not hesitate to speak of and to attempt to study animal cognition. The behavior of organisms is also a legitimate subject matter, and praxics, the study of behavior, has led to significant advances in our understanding of the kinds of behaviors that lead psychologists to speak of cognition. Praxics is a biological science; the attempt by students of behavior to appropriate psychology has been misguided. Generativity theory is an example of a formal theory of behavior that has proved useful both in the engineering of intelligent performances in nonhuman animals and in the prediction of intelligent performances in humans.
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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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Sarter, M. (2004). Animal cognition: defining the issues. Neurosci Biobehav Rev, 28(7), 645–650.
Abstract: The assessment of cognitive functions in rodents represents a critical experimental variable in many research fields, ranging from the basic cognitive neurosciences to psychopharmacology and neurotoxicology. The increasing use of animal behavioral tests as 'assays' for the assessment of effects on learning and memory has resulted in a considerable heterogeneity of data, particularly in the field of behavioral and psycho pharmacology. The limited predictive validity of changes in behavioral performance observed in standard animal tests of learning and memory indicates that a renewed effort to scrutinize the validity of these tests is warranted. In humans, levels of processing (effortful vs. automatic) and categories of information (procedural vs. episodic/declarative) are important variables of cognitive operations. The design of tasks that assess the recall of 'episodic' or 'declarative' information appears to represent a particular challenge for research using laboratory rodents. For example, the hypothesis that changes in inspection time for a previously encountered place or object are based on the recall of declarative/episodic information requires substantiation. In order to generalize findings on the effects of neuronal or pharmacological manipulations on learning and memory, obtained from one species and one task, to other species and other tasks, the mediating role of important sets of variables which influence learning and memory (e.g. attentional, affective) needs to be determined. Similar to the view that a neuronal manipulation (e.g. a lesion) represents a theory of the condition modeled (e.g. a degenerative disorder), an animal behavioral task represents a theory of the behavioral/cognitive process of interest. Therefore, the test of hypotheses regarding the validity of procedures used to assess cognitive functions in animals is an inherent part of the research process.
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de Waal, F. B. M. (2003). Animal communication: panel discussion. Ann N Y Acad Sci, 1000, 79–87.
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Dugatkin, L. A. (2002). Animal cooperation among unrelated individuals. Naturwissenschaften, 89(12), 533–541.
Abstract: The evolution of cooperation has long been a topic near and dear to the hearts of behavioral and evolutionary ecologists. Cooperative behaviors run the gamut from fairly simple to very complicated and there are a myriad of ways to study cooperation. Here I shall focus on three paths that have been delineated in the study of intraspecific cooperation among unrelated individuals: reciprocity, byproduct mutualism, and group selection. In each case, I attempt to delineate the theory underlying each of these paths and then provide examples from the empirical literature. In addition, I shall briefly touch upon some recent work that has attempted to examine (or re-examine) the role of cognition and phylogeny in the study of cooperative behavior. While empirical and theoretical work has made significant strides in the name of better understanding the evolution and maintenance of cooperative behavior in animals, much work remains for the future. “From the point of view of the moralist, the animal world is on about the same level as the gladiator's show. The creatures are fairly well treated, and set to fight; whereby the strongest, the swiftest and the cunningest live to fight another day. The spectator has no need to turn his thumb down, as no quarter is given em leader the weakest and the stupidest went to the wall, while the toughest and the shrewdest, those who were best fitted to cope with their circumstances, but not the best in any other way, survived. Life was a continuous free fight, and em leader a war of each against all was the normal state of existence.” (Huxley 1888)
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Helton, W. S. (2005). Animal expertise, conscious or not. Anim. Cogn., 8(2), 67–74.
Abstract: Rossano (Cognition 89:207, 2003) proposes expertise as an indicator of consciousness in humans and other animals. Since there is strong evidence that the development of expertise requires deliberate practice (Ericsson in The road to excellence: the acquisition of expert performance in the arts and sciences, sports and games 1996), and deliberate practice appears to be outside of the bounds of unconscious processing, then any signs of expertise development in an animal are indicators of consciousness. Rossano's argument may lead to an unsolvable debate about animal consciousness while causing researchers to overlook the underlying reality of animal expertise. This article provides evidence indicative of animals meeting each of the three definitions of expertise established in the scientific literature: expertise as a social construction, expertise as exceptional performance, and expertise as knowledge. In addition, cases of deliberate practice by non-human animals are offered. Acknowledging some animals as experts, regardless of consciousness, is warranted by the research findings and would prove useful in solving many issues remaining in the human expertise literature.
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