Abstract: This paper aims to review a long-term research project exploring the chimpanzee mind within historical and ecological contexts. The Ai project began in 1978 and was directly inspired by preceding ape-language studies conducted in Western countries. However, in contrast with the latter, it has focused on the perceptual and cognitive capabilities of chimpanzees rather than communicative skills between humans and chimpanzees. In the original setting, a single chimpanzee faced a computer-controlled apparatus and performed various kinds of matching-to-sample discrimination tasks. Questions regarding the chimpanzee mind can be traced back to Wolfgang Koehler's work in the early part of the 20th century. Yet, Japan has its unique natural and cultural background: it is home to an indigenous primate species, the Japanese snow monkey. This fact has contributed to the emergence of two previous projects in the wild led by the late Kinji Imanishi and his students. First, the Koshima monkey project began in 1948 and became famous for its discovery of the cultural propagation of sweet-potato washing behavior. Second, pioneering work in Africa, starting in 1958, aimed to study great apes in their natural habitat. Thanks to the influence of these intellectual ancestors, the present author also undertook the field study of chimpanzees in the wild, focusing on tool manufacture and use. This work has demonstrated the importance of social and ecological perspectives even for the study of the mind. Combining experimental approaches with a field setting, the Ai project continues to explore cognition and behavior in chimpanzees, while its focus has shifted from the study of a single subject toward that of the community as a whole.

Abstract: This article reviews the prerequisites for quantitative models of animal learning and cognition, describes the types of models, provides a rationale for the development of such quantitative models, describes criteria for their evaluation, and makes recommendations for the next generation of quantitative models. A modular approach to the development of models is described in which a procedure is considered as a generator of stimuli and a model is considered as a generator of responses. The goal is to develop models that, in combination with many different procedures, produce sequences of times of occurrence of events (stimuli and responses) that are indistinguishable from those produced by the animal under many experimental procedures and data analysis techniques.

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.

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.