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Quesada, J., Kintsch, W., & Gomez, E. (2005). Complex problem-solving: a field in search of a definition? Theor Issues Ergon Sci, 6(1), 5–33.
Abstract: Complex problem-solving (CPS) is as an area of cognitive science that has received a good amount of attention, but theories in the field have not progressed accordingly. The reasons could be the lack of good definitions and classifications of the tasks (taxonomies). Although complexity is a term used pervasively in psychology and is operationalized in different ways, there are no psychological theories of complexity. The definition of problem-solving has been changed in the past to reflect the varied interests of the researchers and has lost its initial concreteness. These two facts together make it difficult to define CPS or make clear if CPS should reuse the theory and methods of classical problem-solving or on the contrary should build a theoretical structure starting from scratch. A taxonomy is offered of tasks using both formal features and psychological features that are theory-independent that could help compare the CPS tasks used in the literature. The adequateness is also reviewed of the most extended definitions of CPS and conclude that they are in serious need of review, since they cover tasks that are not considered problem-solving by their own authors or are not complex, but ignore others that should clearly be included.
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Boyd, L. E., Carbonaro, D. A., & Houpt, K. A. (1988). The 24-hour time budget of Przewalski horses. Appl. Anim. Behav. Sci., 21(1-2), 5–17.
Abstract: A herd of 8 Przewalski horses were observed on pasture in summer. Fifteen-minute focal animal samples were used to determine the time budget of the horses during the periods 00.00-04.00, 04.00-08.00, 08.00-12.00, 12.00-16.00, 16.00-20.00 and 20.00-24.00 h EDT. The behavioral states recorded were feeding (grazing and eating grain), nursing, drinking, standing, stand-resting, self-grooming, mutual grooming, locomoting, playing, and lying laterally and sternally. The average number of behavioral states occurring per hour, and the defecation, urination, aggression and vocalization rates were also determined. Overall, the horses spent 46.4 +/- 5.9% of their time feeding, 1.3 +/- 0.1% nursing, 0.5 +/- 0.1% drinking, 20.6 +/- 5.4% standing, 15.7 +/- 3.2% stand-resting, 1.7 +/- 0.2% self-grooming, 2.2 +/- 0.7% mutual grooming, 7.4 +/- 1.0% locomoting, 1.2 +/- 0.3% playing, 1.2 +/- 0.5% lying laterally and 4.1 +/- 3.0% lying sternally. The horses averaged 45.2 +/- 5.8 behavioral states per hour, and 0.2 +/- 0.0 defecations, 0.3 +/- 0.0 urinations, 1.5 +/- 0.3 aggressions and 0.7 +/- 0.1 vocalizations per hour. The horses spent the greatest amount of time foraging between 20.00 and 04.00 h, when the temperatures were lower. They spent 68.2 +/- 2.2% of their time between 20.00 and 24.00 h feeding, but only 31.2 +/- 2.1% of their time feeding between 08.00 and 12.00 h. Recumbent rest was most common between 00.00 and 04.00 h. As temperatures rose during the daylight hours, the horses spent more time drinking and standing, rather than grazing. Stand-resting was the most common form of rest during the day. The horses exhibited the greatest number of activities per hour from 08.00 to 20.00 h. While standing in close proximity to one another during these hours, the horses exhibited the highest number of aggressions per hour (1.9-2.4).
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Walther, F. R. (1991). On herding behavior. Appl. Anim. Behav. Sci., 29(1-4), 5–13.
Abstract: Herding behavior in ungulates is executed mainly by males. There are several forms of herding: guarding a single estrous female; rounding up a bunch of females during the rutting season; territorial herding by which a male keeps females inside his territory; herding of a moving, permanent, harem group; social herding in which group members of both sexes are herded by one dominant male. When put into this sequence, a phenotypical trend is illustrated, leading from an intimate connection of herding with mating behavior toward an increasing independence from sexual behavior and culminating in a complete socialization of herding. Aspects and problems of herding behavior are the recognition of, and the animal's respect for, partners in gregarious species; the animal “taking offense” at activities of others which deviate from its own activity; the active coordination and synchronization of group activities; the use of, and the effects of, threat, dominance and courtship displays in herding; the possibility of substitution among expressive displays in relation to partners of different sex; the communicative function of the animal's orientation relative to the partner; social hierarchy and leadership in a group; the possibility of interspecific herding, particularly in man-animal relationships, which is closely linked to the process of domestication.
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Sumpter, D. J. T. (2006). The principles of collective animal behaviour. Phil. Trans. Biol. Sci., 361(1465), 5–22.
Abstract: In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.
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Gardner, E. L., & Engel, D. R. (1971). Imitational and social facilitatory aspects of observational learning in the laboratory rat. Psychon. Sci., 25(1), 5–6.
Abstract: Rats acquired a food-motivated leverpressing response by “observational learning” or by trial-and-error learning under conditions of social facilitation or isolation. Both the observational learning and social facilitation Ss learned faster than did the isolated trial-and-error Ss. There was no difference in speed of learning between the observational learning and social facilitation groups. It is suggested that some previous studies purporting to demonstrate observational learning may have demonstrated socially facilitated trial-and-error learning instead.
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Hampton, R. R., Healy, S. D., Shettleworth, S. J., & Kamil, A. C. (2002). Neuroecologists' are not made of straw. Trends. Cognit. Sci., 6(1), 6–7.
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de Waal, F. B. M. (2003). Darwin's legacy and the study of primate visual communication. Ann N Y Acad Sci, 1000, 7–31.
Abstract: After Charles Darwin's The Expression of the Emotions in Man and Animals, published in 1872, we had to wait 60 years before the theme of animal expressions was picked up by another astute observer. In 1935, Nadezhda Ladygina-Kohts published a detailed comparison of the expressive behavior of a juvenile chimpanzee and of her own child. After Kohts, we had to wait until the 1960s for modern ethological analyses of primate facial and gestural communication. Again, the focus was on the chimpanzee, but ethograms on other primates appeared as well. Our understanding of the range of expressions in other primates is at present far more advanced than that in Darwin's time. A strong social component has been added: instead of focusing on the expressions per se, they are now often classified according to the social situations in which they typically occur. Initially, quantitative analyses were sequential (i.e., concerned with temporal associations between behavior patterns), and they avoided the language of emotions. I will discuss some of this early work, including my own on the communicative repertoire of the bonobo, a close relative of the chimpanzee (and ourselves). I will provide concrete examples to make the point that there is a much richer matrix of contexts possible than the common behavioral categories of aggression, sex, fear, play, and so on. Primate signaling is a form of negotiation, and previous classifications have ignored the specifics of what animals try to achieve with their exchanges. There is also increasing evidence for signal conventionalization in primates, especially the apes, in both captivity and the field. This process results in group-specific or “cultural” communication patterns.
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Baker, A. E. M., & Crawford, B. H. (1986). Observational learning in horses. Appl. Anim. Behav. Sci., 15(1), 7–13.
Abstract: This experiment was designed to determine if a horse could learn the location of grain by watching another horse find grain in one of two feed buckets. Both experimental and control groups contained 9 quarter horses consisting of five 2-year-old mares, two 2-year-old geldings, and two 3-year-old geldings. Two mature geldings were used as “demonstrators”. An “experimental” was a horse that could watch three times daily another horse, the “demonstrator”, choose between and eat grain from a black or white bucket, only one of which contained grain. A “control” was a horse that could watch a demonstrator in the same arena for 3 min daily when both feed buckets were removed. When the demonstrator was removed on each of 15 successive days, the experimental or control horse was given five trials to determine if it could find the feed bucket with grain. No significant difference between experimentals and controls occurred for both first and total correct choices and for time to reach the feed bucket with grain. We conclude that no observational learning occurred. This experiment was also used to determine if the identity of horses that learned rapidly by trial and error could be predicted by the time it took to reach the feed bucket with grain. Data from the last three trials of experimentals and controls were combined. Significantly less time to find feed was needed by horses with more than the median number of correct choices. Both number of correct choices and time needed to contact a feed bucket summed over the first 5 days accurately predicted the same data summed over the last 10 days. We conclude that horses that learn rapidly by trial and error make correct choices rapidly, and that these horses can by identified after 5 days of testing.
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Henry, S., Fureix, C., Rowberry, R., Bateson, M., & Hausberger, M. (2017). Do horses with poor welfare show 'pessimistic' cognitive biases? Sci. Nat., 104(1), 8.
Abstract: This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations (e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions (e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food ('positive' location) or unpalatable food ('negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.
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McGreevy, P. D., McLean, A. N., Warren-Smith, A. K., Waran, N., & Goodwin, D. (2005). Defining the terms and processes associated with equitation. Proceedings of the First International Equitation Science Symposium, , 10–43.
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