Exemplar-based accounts of "multiple-system" phenomena in perceptual categorization

We demonstrate that a wide variety of recently reported "rule-described" and "prototype-described" phenomena in perceptual classification, which have led to the development of a number of multiple-system models, can be given an alternative interpretation in terms of a single-system exemplar-similarity model. The phenomena include various rule- and prototype-described patterns of generalization, dissociations between categorization and similarity judgments, and dissociations between categorization and old-new recognition. The alternative exemplar-based interpretation relies on the idea that similarity is not an invariant relation but a context-dependent one. Similarity relations among exemplars change systematically because of selective attention to dimensions and because of changes in the level of sensitivity relating judged similarity to distance in psychological space. Adaptive learning principles may help explain the systematic influence of the selective attention process and of modulation in sensitivity settings on judged similarity.     

Internalization: a metaphor we can live without

Shepard has supposed that the mind is stocked with innate knowledge of the world and that this knowledge figures prominently in the way we see the world. According to him, this internal knowledge is the legacy of a process of internalization; a process of natural selection over the evolutionary history of the species. Shepard has developed his proposal most fully in his analysis of the relation between kinematic geometry and the shape of the motion path in apparent motion displays. We argue that Shepard has made a case for applying the principles of kinematic geometry to the perception of motion, but that he has not made the case for injecting these principles into the mind of the percipient. We offer a more modest interpretation of his important findings: that kinematic geometry may be a model of apparent motion. Inasmuch as our recommended interpretation does not lodge geometry in the mind of the percipient, the motivation of positing internalization, a process that moves kinematic geometry into the mind, is obviated. In our conclusion, we suggest that cognitive psychologists, in their embrace of internal mental universals and internalization may have been seduced by the siren call of metaphor.     

Applying Science and Applied Science: What’s the Difference?

Prandtl’s work on the boundary layer theory is an interesting example for illustrating several important issues in philosophy of science such as the relation between theories and models and whether it is possible to distinguish, in a principled way, between pure and applied science. In what follows I discuss several proposals by the symposium participants regarding the interpretation of Prandtl’s work and whether it should be characterized as an instance of applied science. My own interpretation of this example (1999) emphasised the degree of autonomy embedded in Prandtl’s boundary layer model and the way it became integrated in the larger theoretical context of hydrodynamics. In addition to extending that discussion here I also claim that the characterization of applied science which formed the basis for the symposium does not enable us to successfully distinguish applied science from the general practice of ‘applying’ basic scientific knowledge in a variety of contexts.     

Theory of constructions and set in problem solving

Hierarchically organized knowledge about actions has been postulated to explain planning in problem solving. Perdix, a simulation of problem solving in geometry with schematic planning knowledge, is described. Perdix’s planning knowledge enables it to augment the problem space it is given by constructing auxiliary lines. The planning system also provides a mechanism that can result in problem solving set. Results of three experiments involving set and constructions seem consistent with the kinds of knowledge structures hypothesized in the model. Protocols given during solution of 11 geometry problems showed general agreement with the explanation of constructions and set based on planning knowledge, but they also indicated processes of human problem solving not represented in the model. Finally, the explanation of constructions is discussed in relation to the general question of ill-structured problems and creativity, and the explanation of set is discussed in relation to other phenomena in the problem solving literature, including functional fixedness.     

有多少记忆可以内隐——兼评Jacoby加工分离程序

自从1991Jacoby使用简单的再认任务分离出意识性提取与无意识熟悉性以来,虽然PDP的计算范式也受到一些修正,但均没有在计算范式的内核思想上改进过,只是PDP延伸出的应用研究非常多。其实,Jacoby在构建PDP范式时,从描述PDP的心理现象、构建数学模型到PDP在实践中的应用上均出现了重大失误。本研究从上述三个方面对PDP提出了质疑,使用集合模型重新构建了PDP计算模型,用实验验证了PDP新模型,纠正了Jacoby理论与应用的三大错误。     

What drives the organization of object knowledge in the brain?

Various forms of category-specificity have been described at both the cognitive and neural levels, inviting the inference that different semantic domains are processed by distinct, dedicated mechanisms. In this paper, we argue for an extension of a domain-specific interpretation to these phenomena that is based on network-level analyses of functional coupling among brain regions. On this view, domain-specificity in one region of the brain emerges because of innate connectivity with a network of regions that also process information about that domain. Recent findings are reviewed that converge with this framework, and a new direction is outlined for understanding the neural principles that shape the organization of conceptual knowledge.     

Autoshaping and automaintenance: a neural-network approach

This article presents an interpretation of autoshaping, and positive and negative automaintenance, based on a neural-network model. The model makes no distinction between operant and respondent learning mechanisms, and takes into account knowledge of hippocampal and dopaminergic systems. Four simulations were run, each one using an A-B-A design and four instances of feedfoward architectures. In A, networks received a positive contingency between inputs that simulated a conditioned stimulus (CS) and an input that simulated an unconditioned stimulus (US). Responding was simulated as an output activation that was neither elicited by nor required for the US. B was an omission-training procedure. Response directedness was defined as sensory feedback from responding, simulated as a dependence of other inputs on responding. In Simulation 1, the phenomena were simulated with a fully connected architecture and maximally intense response feedback. The other simulations used a partially connected architecture without competition between CS and response feedback. In Simulation 2, a maximally intense feedback resulted in substantial autoshaping and automaintenance. In Simulation 3, eliminating response feedback interfered substantially with autoshaping and automaintenance. In Simulation 4, intermediate autoshaping and automaintenance resulted from an intermediate response feedback. Implications for the operant-respondent distinction and the behavior-neuroscience relation are discussed.     

The task-specific nature of domain-general reasoning

This paper develops a theory of how interpretative processes constrain inferential performance on conditional reasoning tasks. Experiment 1 investigated the hypothesis that performance on common reasoning tasks is mediated by different interpretive variables. Necessity and sufficiency relations predicted performance on the conditional arguments task, whereas on the Wason task, performance was predicted by whether the conditional statement instantiated a deontic or a factual relation. Performance on the truth-table task was predicted by both sets of variables. Experiment 2 explored the mapping relation between interpretation, representation, and inference. It was observed that conditional responses to the Wason and arguments tasks were based on different representations of the conditional relationship. These data rule out a simple model of the interplay between interpretation and reasoning in which the interpretation of a statement is driven solely by its content, and instead, indicate that the interpretation of conditional relations is task-specific.     

INTERPRETIVE PRAXIS AND THEORY-NETWORKS

Abstract:  I develop the idea of what I call an interpretive praxis as a generalized procedure for analyzing how experimenters can formulate observable predictions, discern real effects from experimental artifacts, and compare predictions with data. An interpretive praxis requires theories – theories not only about instruments and the interpretation of phenomena, but also theories that connect the use of instruments and interpretation of phenomena to high-level theory. I will call all such theories that enable experimentation to work intermediate theories . I offer an account of theory-networks that embrace these intermediate theories and explain their functions.     

What kind of knowledge is necessary for the interpretation of language?

An investigation into what kind of knowledge is necessary for interpretation is an important research project for the two fields of the theory of meaning and epistemology, through which they are combined. By examining the two basic requirements for a theory on the interpretation of language drafted by Donald Davidson, this paper analyzes several kinds of knowledge which are necessary for interpretation. The goal is to explore the knowledge of radical interpretation and the distinctions and connections between this knowledge and radical translation and Convention-T, thus revealing its characteristics and possibility to interpretation.     

语言诠释需要什么样的知识?

An investigation into what kind of knowledge is necessary for interpretation is an important research project for the two fields of the theory of meaning and epistemology, through which they are combined. By examining the two basic requirements for a theory on the interpretation of language drafted by Donald Davidson, this paper analyzes several kinds of knowledge which are necessary for interpretation. The goal is to explore the knowledge of radical interpretation and the distinctions and connections between this knowledge and radical translation and Convention-T, thus revealing its characteristics and possibility to interpretation.     

Cue interaction effects in causal judgement: An interpretation in terms of the evidential evaluation model

In judging the extent to which a cue causes an outcome, judgement can be affected by information about other cues that are correlated with the one being judged. These cue interaction effects have usually been interpreted in terms of associative learning processes. I propose that a different model of causal judgement, the evidential evaluation model, offers a viable alternative interpretation of cue interaction phenomena. Under the evidential evaluation model, instances of contingency information are interpreted as evidence, which is confirmatory, disconfirmatory, or irrelevant for the cue being judged. When two cues co-occur in a set of instances the evidential value of the instances for one of them is determined by three factors: the proportion of confirming instances in the set; disambiguation value, which concerns the relation between the set of information and prior beliefs about the co-occurring cue; and confirmation value, which concerns the relation between the set of information and prior beliefs about the cue being judged. Any previous judgement of the cue is then modified in the light of these. It is shown that this model can account for all the cue interaction phenomena that have been investigated in studies of human causal judgement. The model also generates novel predictions, and the results of three experiments give support to these predictions. It is also shown that several other current models of causal judgement fail to predict a key result from Experiment 3.     

The theory of the organism-environment system: III. Role of efferent influences on receptors in the formation of knowledge

The present article is an attempt to give—in the frame of the theory of the organism-environment system (jarvilehto, 1998a)—a new interpretation to the role of efferent influences on receptor activity and to the functions of senses in the formation of knowledge. It is argued, on the basis of experimental evidence and theoretical considerations, that the senses are not transmitters of environmental information, but create a direct connection between the organism and the environment, which makes the development of a dynamic living system, the organism-environment system, possible. In this connection process, the efferent influences on receptor activity are of particular significance because, with their help, the receptors may be adjusted in relation to the parts of the environment that are most important in achieving behavioral results. Perception is the process of joining of new parts of the environment to the organism-environment system; thus, the formation of knowledge by perception is based on reorganization (widening and differentiation) of the organism-environment system, and not on transmission of information from the environment. With the help of the efferent influences of receptors, each organism creates its own peculiar world that is simultaneously subjective and objective. The present considerations have far-reaching influences as well on experimental work in neurophysiology and psychology of perception as on philosophical consideration of knowledge formation.     

The role of support in psychoanalysis.

A two-factor theory of clinical psychoanalysis is proposed. In accordance with the predominant position of the structural-adaptational ("classical") approach in psychoanalytic theory, the power of interpretation and insight in clinical psychoanalysis has received ample attention in psychoanalytic literature. There seems, however, to be a growing awareness among analysts that not all the facts of an analytic treatment can be accounted for by this approach alone. A second factor is increasingly recognized: the power of adequate support provided by the analyst and resulting in a specific experience by the analysand. In the application of the developmental ("postclassical") approach of psychoanalytic theory, the importance of this support-experience factor in the treatment of ordinary neurosis by means of ordinary psychoanalysis is emphasized. The relative neglect of this aspect of clinical psychoanalysis may be indicative of the present-day dilemma of how to translate advances in theoretical knowledge of mental development into the therapeutic praxis of psychoanalysis. There may, however, be another important reason. Support and experience are phenomena often occurring on the nonverbal level. In contrast to interpretation and insight, they are usually not voiced, let alone distinctly and loudly expressed. They are the silent power of psychoanalysis.     

Integrating analogical mapping and general problem solving: the path-mapping theory

This article describes the path-mapping theory of how humans integrate analogical mapping and general problem solving. The theory posits that humans represent analogs with declarative roles, map analogs by lower-level retrieval of analogous role paths, and coordinate mappings with higher-level organizational knowledge. Implemented in the ACT-R cognitive architecture, the path-mapping theory enables models of analogical mapping behavior to incorporate and interface with other problem-solving knowledge. Path-mapping models thus can include task-specific skills such as encoding analogs or generating responses, and can make behavioral predictions at the level of real-world metrics such as latency or correctness. We show that the path-mapping theory can successfully account for the major phenomena addressed by previous theories of analogy. We also describe a path-mapping model that can account for subjects' incremental eye-movement and typing behavior in a story-mapping task. We discuss extensions and implications of this work to other areas of analogy and problem-solving research.     

A model theory of induction

Theories of induction in psychology and artificial intelligence assume that the process leads from observation and knowledge to the formulation of linguistic conjectures. This paper proposes instead that the process yields mental models of phenomena. It uses this hypothesis to distinguish between deduction, induction, and creative forms of thought. It shows how models could underlie inductions about specific matters. In the domain of linguistic conjectures, there are many possible inductive generalizations of a conjecture. In the domain of models, however, generalization calls for only a single operation: the addition of information to a model. If the information to be added is inconsistent with the model, then it eliminates the model as false: this operation suffices for all generalizations in a Boolean domain. Otherwise, the information that is added may have effects equivalent (a) to the replacement of an existential quantifier by a universal quantifier, or (b) to the promotion of an existential quantifier from inside to outside the scope of a universal quantifier. The latter operation is novel, and does not seem to have been used in any linguistic theory of induction. Finally, the paper describes a set of constraints on human induction, and outlines the evidence in favor of a model theory of induction.     

A statistical description of verbal learning

Free-recall verbal learning is analyzed in terms of a probability model. The general theory assumes that the probability of recalling a word on any trial is completely determined by the number of times the word has been recalled on previous trials. Three particular cases of this general theory are examined. In these three cases, specific restrictions are placed upon the relation between probability of recall and number of previous recalls. The application of these special cases to typical experimental data is illustrated. An interpretation of the model in terms of set theory is suggested but is not essential to the argument.