The general process view of learning, which guided research into learning for the first half of this century, has come under attack in recent years from several quarters. One form of criticism has come from proponents of the so-called biological boundaries approach to learning. These theorists have presented a variety of data showing that supposedly general laws of learning may in fact be limited in their applicability to different species and learning tasks, and they argue that the limitations are drawn (...) by the nature of each species' adaptation to the particular requirements of its natural environment. The biological boundaries approach has served an important critical function in the move away from general process learning theory, but it is limited in its ability to provide an alternative to the general process approach. In particular, the biological boundaries approach lacks generality, it is in some respects subservient to the general process tradition, and its ecological content is in too many cases limited toex post factoadaptive explanations of learning skills. A contrasting, ecological approach to learning, which can provide a true alternative to general process theory, is presented. The ecological approach begins by providing an ecological task description for naturally occurring instances of learning; this step answers the question:Whatdoes this animal learn to do? The next step is an analysis of the means by which learning occurs in the course of development, answering the question:Howdoes the animal learn to do this? On the basis of such analyses, local principles of adaptation are formulated to account for the learning abilities of individual species. More global principles are sought by generalization among these local principles and may form the basis for a general ecological theory of learning. (shrink)

To study animal welfare empirically we need an objective basis for deciding when an animal is suffering. Suffering includes a wide range ofunpleasant emotional states such as fear, boredom, pain, and hunger. Suffering has evolved as a mechanism for avoiding sources ofdanger and threats to fitness. Captive animals often suffer in situations in which they are prevented from doing something that they are highly motivated to do. The an animal is prepared to pay to attain or to escape a situation (...) is an index ofhow the animal about that situation. Withholding conditions or commodities for which an animal shows (i.e., for which it continues to work despite increasing costs) is very likely to cause suffering. In designing environments for animals in zoos, farms, and laboratories, priority should be given to features for which animals show inelastic demand. The care ofanimals can thereby be based on an objective, animal-centered assessment of their needs. (shrink)

Maximization theory, which is borrowed from economics, provides techniques for predicing the behavior of animals - including humans. A theoretical behavioral space is constructed in which each point represents a given combination of various behavioral alternatives. With two alternatives - behavior A and behavior B - each point within the space represents a certain amount of time spent performing behavior A and a certain amount of time spent performing behavior B. A particular environmental situation can be described as a constraint (...) on available points (a circumscribed area) within the space. Maximization theory assumes that animals always choose the available point with the highest numerical value. The task of maximization theory is to assign to points in the behavioral space values that remain constant across various environmental situations; as those situations change, the point actually chosen is always the one with the highest assigned value. (shrink)

Effective conditioning requires a correlation between the experimenter's definition of a response and an organism's, but an animal's perception of its behavior differs from ours. These experiments explore various definitions of the response, using the slopes of learning curves to infer which comes closest to the organism's definition. The resulting exponentially weighted moving average provides a model of memory that is used to ground a quantitative theory of reinforcement. The theory assumes that: incentives excite behavior and focus the excitement on (...) responses that are contemporaneous in memory. The correlation between the organism's memory and the behavior measured by the experimenter is given by coupling coefficients, which are derived for various schedules of reinforcement. The coupling coefficients for simple schedules may be concatenated to predict the effects of complex schedules. The coefficients are inserted into a generic model of arousal and temporal constraint to predict response rates under any scheduling arrangement. The theory posits a response-indexed decay of memory, not a time-indexed one. It requires that incentives displace memory for the responses that occur before them, and may truncate the representation of the response that brings them about. As a contiguity-weighted correlation model, it bridges opposing views of the reinforcement process. By placing the short-term memory of behavior in so central a role, it provides a behavioral account of a key cognitive process. (shrink)