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The authors make a distinction between instrumental copying behavior in which there is a clear reward for the copying behavior and social copying (traditions) in which the rewards for copying are less clear. However, I see no reason to distinguish between the two. We are social animals, for whom copying traditions have important rewards, those of affiliation.
Framing effects attributed to “quasi-cyclical” irrational complex human preferences are ubiquitous biases resulting from simpler mechanisms that can be found in other animals. Examples of such framing effects vary from simple learning contexts, to an analog of human gambling behavior, to the value added to a reinforcer by the effort that went into obtaining it.
The ability to assess the intelligence of other species has been constrained because it is not always easy to communicate to other species what we require of them. Furthermore, we tend to define the tasks with procedures designed for us rather than for the species in question. The appropriate assessment of animal intelligence is important, however, because it has demonstrated that although the human capacity for intelligent behavior quantitatively surpasses that of other animals, qualitatively, it is not as different as we generally believe. Furthermore, the intelligent behavior of other species demonstrates that although language and culture contribute to human intelligence, they are clearly not necessary. Finally, although we attribute certain human behavior such as unskilled gambling and cognitive dissonance to our complex social environment, the fact that other species show very similar suboptimal behavior suggests that simpler underlying processes likely are responsible for those behaviors.
This chapter discusses a core problem that has plagued the study of intelligence for decades, the complexity of behavior. The central tenets of dynamic systems, which underpin efforts to analyze the organization and development of behavior in its complexity are outlined, keeping person and context connected and treating variability as the starting point for analysis. The classic approaches to intelligence, psychometric, Piagetian, nativist, and dynamic/constructivist are reviewed. The chapter explains how disputes between them have illuminated learning sequences, resolved important questions, and paved the way for a dynamic approach to intelligence are shown. The dynamic skill theory framework, emphasizing its conceptual origins in dynamic systems, ways that it has advanced understanding variability and consistency in intelligence, and its relevance to understanding childhood intelligence are introduced. The areas where dynamic systems concepts and models have generated usable knowledge directly relevant to intelligence, learning, and the practice of education are considered.
Rachlin proposes that the mechanism underlying self-control involves the cost incurred in changing one's response pattern, but his account explains neither how the response pattern is originally established nor why a change in response pattern entails a cost. I suggest that response patterns occur because they tend to be effective (thus alternatives are more costly) and are maintained because the decision process itself is costly.
The authors' attempt to explore the ability of animals to monitor how certain they are of their choice behavior, necessarily fails both in their effort to include “higher” mammals (such as monkeys and dolphins) in the class of metacognitive organisms (humans) and in their conclusion that “lower” organisms are not capable of similar behavior.
The dance metaphor for the communication between two organisms may be an appealing image because it appears to capture the intricate synchronization of their interaction; however, it is neither parsimonious nor easily tested. Instead, a multichannel information-processing model, even one that can process only serial events, provides all of the flexibility required to account for the complex temporal coordinated action observed.
It is assumed that self-control always has a higher value. What if it does not? Furthermore, although there are clearly intrinsic reinforcers, their measurement is problematic, especially for a behavioral analyst. Finally, is it more parsimonious to postulate that these behaviors are acquired rather than genetically based?
With some justification, humans place themselves at the top of the evolutionary scale. If we rule out the exceptional sensory and response skills of certain nonhuman animals, clearly the sum of our intellectual capacity, measured in almost any way, exceeds that of other animals. The role of our intelligence in the domination of our species over others is clear, but in the broader perspective of evolution, intelligence per se can be viewed quite differently. Our species-centric view of intelligence may be self-serving, but as a general characteristic it correlates only superficially (and perhaps even negatively) with most measures of evolutionary success.
Survival, or more specifically, survival of the genes (Dawkins, 1976) is the measure of evolutionary success. From a purely biological perspective, the ideal survival “machine” is a simple, perhaps one-celled, organism (e.g., bacteria). By some estimates, bacteria, in spite of their small size, account for as much biomass as all other life forms combined, including plants (Gould, 1996). The survival strategy of bacteria is to reproduce quickly and often with sufficient genetic variability to accommodate changes in the environment. This has proven to be a very effective strategy also for more complex organisms like insects and many fishes. An alternative strategy is to invest more in the genetic carrier (the individual organism) and to build within the organism the flexibility required for survival.
Intelligence, in its simplest form, can be thought of as the built-in flexibility that allows individual organisms to adjust their behavior to relatively rapidly changing environments (Stenhouse, 1974, p. 61).
Byrne & Russon propose that priming can account for the
imitation of simple actions, but they fail to explain how the behavior
of another can prime the observer's own behavior. They also
propose that imitation of complex skills requires a sequence of acts
tied together by a program, but they fail to rule out the role of
trial-and-error learning and perceptual/motivational mechanisms
in such task acquisition.
Heyes discounts findings of imitation and self recognition in
nonhuman primates based on flimsy speculation and then indicates that
even positive findings would not provide evidence of theory of mind.
Her proposed experiment is unlikely to work, however, because, even if
the animals have a theory of mind, a number of assumptions, not
directly related to theory of mind, must be made about their reasoning
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