Dissociable learning processes, associative theory, and testimonial reviews: A comment on Smith and Church (2018)

1-Back reinforcement symbolic-matching by humans: How do they learn it?

For humans, a distinction has been made between implicit and explicit learning. Implicit learning is thought to involve automatic processes of the kind involved in much Pavlovian conditioning, while explicit learning is thought to involve conscious hypothesis testing and rule formation, in which the subject's statement of the rule has been taken as evidence of explicit learning. Various methods have been used to determine if nonverbal animals are able to learn a task explicitly - among these is the 1-back reinforcement task in which feedback from performance on the current conditional discrimination trial is provided only after completion of the following trial. We propose that it is not whether an organism can learn the task, but whether they learn it rapidly, all-or-none, that provides a better distinction between the two kinds of learning. We had humans learn a symbolic matching, 1-back reinforcement task. Almost half of the subjects failed to learn the task, and of those who did, none described the 1-back rule. Thus, it is possible to learn this task without learning the 1-back rule. Furthermore, the backward learning functions for humans differ from those of pigeons. Human subjects who learned the task did so all-or-none, suggesting explicit learning. In earlier research with pigeons, they too showed significant learning of this task; however, backward learning functions suggested that they did so gradually over the course of several sessions of training and to a lower level of asymptotic accuracy than the humans, a result suggesting implicit learning was involved.

Applying Insights on Categorisation, Communication, and Dynamic Decision-Making: A Case Study of a ‘Simple’ Maritime Military Decision

A complete understanding of decision-making in military domains requires gathering insights from several fields of study. To make the task tractable, here we consider a specific example of short-term tactical decisions under uncertainty made by the military at sea. Through this lens, we sketch out relevant literature from three psychological tasks each underpinned by decision-making processes: categorisation, communication and choice. From the literature, we note two general cognitive tendencies that emerge across all three stages: the effect of cognitive load and individual differences. Drawing on these tendencies, we recommend strategies, tools and future research that could improve performance in military domains – but, by extension, would also generalise to other high-stakes contexts. In so doing, we show the extent to which domain general properties of high order cognition are sufficient in explaining behaviours in domain specific contexts.

1-Back reinforcement matching and mismatching by pigeons: Implicit or explicit learning?

In human learning a distinction has been made between implicit and explicit learning. Implicit learning is thought involve automatic processes of the kind involved in Pavlovian conditioning, while explicit learning is thought to involve conscious hypothesis testing and rule formation, in which the ability to report the rule used to learn the task is taken as evidence. Because non-verbal animals cannot provide such evidence, several indirect methods have been proposed. One of these methods is faster learning by humans of certain explicitly learned tasks than implicitly learned tasks, but pigeons do not show a similar difference. Another method involves the 1-back-reinforcement conditional discrimination (if A choose X, if B choose Y) in which feedback following the conditional response is delayed until the next trial. It has been argued that implicit learning cannot occur over the delay between the conditional response and the reinforcer on the next trial, yet, it has been found that monkeys can learn this 1-back reinforcement task. We have argued that such learning can occur implicitly. We have found that pigeons, a species not thought to learn explicitly, can show significant learning of both 1-back reinforcement matching and 1-back reinforcement mismatching, two versions of the 1-back-reinforcement conditional discrimination. We propose that the evidence for explicit learning by non-verbal animals suffers from alternative simpler accounts because the rationale for explicit learning is based on assumptions that likely are not correct.

Pigeons acquire the 1-back task: Implications for implicit versus explicit learning?

In humans, a distinction can be made between implicit or procedural learning (involving stimulus-response associations) and explicit or declarative learning (involving verbalizable rules) that is relatively easy to make in verbal humans. According to several investigators, it is also possible to make such a distinction in nonverbal animals. One way is by training them on a conditional discrimination task (e.g., matching-to-sample) in which reinforcement for correct choice on the current trial is delayed until after a choice is made on the next trial - a method known as the 1-back procedure. According to Smith, Jackson, and Church ( Journal of Comparative Psychology, 134(4), 423-434, 2020), the delay between the sample-correct-comparison response on one trial and reinforcement obtained on the next trial is too long for implicit (associative) learning. Thus, according to this theory, learning must be explicit. In the present experiments we trained pigeons using the 1-back procedure. In Experiment 1, pigeons were trained on red/green 1-back matching using a non-correction procedure. Some of the pigeons showed significant learning. When a correction procedure was introduced, all the pigeons showed evidence of learning. In Experiment 2, new pigeons learned red/green 1-back matching with the correction procedure. In Experiment 3, new pigeons learned symbolic 1-back matching with yellow and blue conditional stimuli and red/green choice stimuli. Thus, pigeons can learn using 1-back reinforcement. Although it would appear that the pigeons acquired this task explicitly, we believe that this procedure does not adequately distinguish between implicit and explicit learning.

The Comparative Psychology of Intelligence: Some Thirty Years Later

After re-reading Macphail's (1987) essay "The Comparative Psychology of Intelligence" with all the associated commentaries, I was struck by how contemporary many of the arguments and counter-arguments still appear. Of course, we now know much more about the abilities of many more species (including their neurobiology) and fewer researchers currently favor explanations of behavior based solely on associative processes; however, the role of contextual variables in comparative psychology still remains cloudy. I discuss these issues briefly. Given my research interests involving the cognitive and communicative abilities of Grey parrots, the one aspect of the original article upon which I feel I can comment in depth involves Macphail's claims about the importance of language-and specifically syntax-in problem-solving and thus in placing humans above all other creatures. Granted, no other species has (or in my opinion is likely ever to acquire) everything that goes into what is considered "human language." Nevertheless, several other species have acquired symbolic representation, and considerable information now exists upon which to base an argument that such acquisition by itself enables more complex and "human-like" cognitive processes. Such processes may form the basis of the kind of intelligence that is measured-not surprisingly-with human-based tasks, including the use of such representations as a means to directly query non-human subjects in ways not unlike those used with young children.

A dimensional summation account of polymorphous category learning

Polymorphous concepts are hard to learn, and this is perhaps surprising because they, like many natural concepts, have an overall similarity structure. However, the dimensional summation hypothesis (Milton and Wills Journal of Experimental Psychology: Learning, Memory and Cognition, 30, 407-415 2004) predicts this difficulty. It also makes a number of other predictions about polymorphous concept formation, which are tested here. In Experiment 4, we confirm the theory's prediction that polymorphous concept formation should be facilitated by deterministic pretraining on the constituent features of the stimulus. This facilitation is relative to an equivalent amount of training on the polymorphous concept itself. In further experiments, we compare the predictions of the dimensional summation hypothesis with a more general strategic account (Experiment 2), a seriality of training account (Experiment 3), a stimulus decomposition account (also Experiment 3), and an error-based account (Experiment 4). The dimensional summation hypothesis provides the best account of these data. In Experiment 5, a further prediction is confirmed-the single feature pretraining effect is eliminated by a concurrent counting task. The current experiments suggest the hypothesis that natural concepts might be acquired by the deliberate serial summation of evidence. This idea has testable implications for classroom learning.