Acquisition Of Rules Research Articles

Dissociation of ketamine effects on rule acquisition and rule implementation: possible relevance to NMDA receptor contributions to executive cognitive functions

Background: The demands of the Wisconsin Card Sorting Test (WCST) change with experience. This report contains two studies designed to examine N-methyl- d-aspartate (NMDA) receptor contributions to the executive components of WCST performance. These aspects of WCST performance figure more prominently in the initial completion of this task than in subsequent task repetitions in healthy populations. Methods: In the first study, healthy subjects ( n = 15) completed the WCST on two occasions separated by 1 week. In the second study, healthy subjects ( n = 22) completed two test days spaced by approximately 1 week, during which, they completed the WCST and other assessments after administration of the NMDA antagonist ketamine (intravenous bolus 0.26 mg/kg followed by infusion of 0.65 mg/kg/hour) or matched placebo. Results: In the first study, subjects reduced the number of total and perseverative errors with a single repetition of the WCST. In the second study, ketamine significantly increased the number of total errors and the number and percent of perseverative errors on the first, but not the second test day. Similarly, it reduced the number of category criteria met on the first, but not second test day. Ketamine also increased distractibility, impaired recall, produced psychosis, altered perception, and had effects resembling the negative symptoms of schizophrenia. However, only WCST performance showed order dependency. Conclusions: This order dependency further implicates NMDA receptors in executive cognitive functions associated with the frontal cortex.

Caudate nucleus abnormalities in first episode psychosis

Frontotemporal dementia (FTD) is classically considered to be a neurodegenerative disease with cortical changes. Recent structural imaging findings, however, highlight that subcortical and in particular striatal regions are also affected in the FTD syndrome. The influence of striatal pathology on cognitive and behavioural changes in FTD is virtually unexplored. In the current study we employ the Weather Prediction Task (WPT), a probabilistic learning task which taps into striatal dysfunction, in a group of FTD patients. We also regressed the patients' behavioural performance with their grey matter atrophy via voxel-based morphometry (VBM) to identify the grey matter contributions to WPT performance in FTD. Based on previous studies we expected to see striatal and frontal atrophy to be involved in impaired probabilistic learning. Our behavioural results show that patients performed on a similar level to controls overall, however, there was a large variability of patient performance in the first 30 trials of the task, which are critical in the acquisition of the probabilistic learning rules. A VBM analysis covarying the performance for the first 30 trials across participants showed that atrophy in striatal but also frontal brain regions correlated with WPT performance in these trials. Closer inspection of performance across the first 30 trials revealed a subgroup of FTD patients that performed significantly poorly than the remaining patients and controls on the WPT, despite achieving the same level of probabilistic learning as the other groups in later trials. Additional VBM analyses revealed that the subgroup of FTD patients with poor early probabilistic learning in the first 30 trials showed greater striatal atrophy compared to the remaining FTD patients and controls. These findings suggest that the integrity of fronto-striatal regions is important for probabilistic learning in FTD, with striatal integrity in particular, determining the acquisition learning rate. These findings will therefore have implications for developing an easily administered version of the probabilistic learning task which can be used by clinicians to assess striatal functioning in neurodegenerative syndromes.

Promotion Rules and Skill Acquisition: An Experimental Study

Standard economic theory identifies a trade-off between up-or-stay and up-or-out promotion rules. Up-or-stay never wastes the skills of those not promoted but may provide insufficient incentives to invest in skills. Up-or-out can always induce investment in skill acquisition but may waste the skills of those not promoted. The paper reports an experiment designed to study this trade-off. Under up-or-out, parties behave almost exactly as theory predicts. But under up-or-stay (and stay-or-stay), results differ markedly from theoretical predictions. In that case workers invest rather frequently, although the prediction is that they would not. These deviations can be explained by various reciprocity mechanisms.

Fuzzy Rule Acquisition from Trained Artificial Neural Networks

We approach the problem of rule extraction in its primary form. That is, given a trained artificial neural network, we extract rules classifying data set as correctly as possible. Attention is oriented toward extraction of fuzzy rules. The choice of fuzzy rules underlines the aim of balancing rule comprehensibility and complexity. To achieve higher comprehensibility of extracted rules, the formulated theoretical material is an extension of crisp rule extraction 1). A rule extraction algorithm is introduced. The presented algorithm for fuzzy rule extraction implies from the derived theoretical results rather than from heuristics. The rule extraction algorithm incorporates a ’built-in’ rule simplification mechanism. This feature is beneficial in cases when trained neural network structure is overdetermined for a given task. The rule extraction algorithm is experimentally demonstrated. Demonstrations incorporate both structure modification training and fixed structure training.

Acquisition of Scheduling Rules by Inductive Learning and Rule Based Local Search

It is important in developing intelligent scheduling systems to build an effective method for acquisition of decision rules. We have proposed a method for acquisition of scheduling rules by using inductive learning. Cases needed for rule acquisition are generated by interchanging two jobs in a sample schedule, and job attributes and location properties of jobs are used as the basic information for the rule acquisition. The proposed method for rule acquisition has been applied to single machine problems and flowshop problems.This paper extends the authors' previous work to jobshop scheduling problems and describes a method to acquire scheduling rules by generating a number of sample schedules and analyzing their properties. The effectiveness of the proposed method for rule acquisition and the applicability of such obtained rules are demonstrated by applying them to the exploration process of local search.

ファジィクラスタリングを用いたファジィID3と制御ルール獲得への応用

ファジィクラスタリングを用いたファジィID3と制御ルール獲得への応用

Refining fuzzy control rules for the inverted double pendulum system based on a transformation-type genetic algorithm

We have been studying fuzzy control of the inverted double pendulum in computer simulations. We can control the inverted double pendulum by fuzzy control rules acquired by trial and error. In this research, we attempted to acquire fuzzy control knowledge for the double pendulum automatically by using a genetic algorithm (GA). In order to adjust the rules of attitude and position control of the double pendulum by the GA, we regarded rule acquisition as a multiobjective optimization problem and formulated hierarchical control knowledge. This paper proposes a new method of treating hierarchical control knowledge by expanding the GA with a local improvement mechanism. This method, based on genetic transformation in microorganisms, allows us to acquire better fuzzy control knowledge of the double pendulum. © 1998 Scripta Technica, Syst Comp Jpn, 29(14): 50–57, 1998

Acquiring Behavioral Rules for Action-Based Robot Environments

We propose a working environment frame for actionbased robots and describe learning for behavioral rule acquisition enabling robots to operate in such an environment. Robot geometric information is expressed in the frame, as the interaction of a potential distribution and robot behavior as potential energy. Potential representation for the multiple constraint satisfaction problem of multiple agents is described, then a simple soccer game situation applied as an example of simulation. In the potential distribution environment, the potential view is observed as sensor input to a robot. The robot decides its own behavior based on this view. To adaptively acquire behavioral rules, a classifier system is applied whose condition is an observed potential view, and a series of condition-action rules is acquired to attain the goal. The effectiveness of the proposed method is demonstrated by computer simulation.

Effect of cooperative learning on the acquisition of second language rules and mechanics

This article reports the results of an experimental investigation of the effect of cooperative learning on the acquisition of English as a second language (ESL) rules and mechanics. Four fourth-grade, four fifth-grade, and four sixth-grade intact classes ( n = 318 students) were randomly assigned to experimental and control conditions. The experimental classes received instruction according to the cooperative learning method of Student Teams Achievements Division, whereas the control classes followed an individualistic instructional approach based on exercises in their regular textbooks. Students were pre-tested and post-tested on their knowledge of ESL rules and mechanics. Results of a two-way analysis of covariance indicated that there was no overall significant interaction between participants' aptitude and their subsequent linguistic achievement. Similarly, there was no significant difference between the control and experimental groups on the post-tests that measured content covered during the period of investigation. However, low achievers in the experimental classes made more relative gains than their high-achieving counterparts in the same classes though not at the expense of the latter.

The Implicit versus Explicit Division in Language Learning Theory, Method, and Practice

The role of grammar in the second classroom has been questioned in recent years. This uncertainty may be due in part to the rapid succession of contemporary acquisition theories and methods. For example, the grammartranslation method of the late nineteenth and the early twentieth centuries viewed grammar rules as the object of study, whereas audiolingualism, strongly influenced by Burrhus E Skinner's behaviorist view of learning, preferred habit formation to explicit grammatical rules (Lado). While the rationalist approach to learning theory stresses the importance of internal mental activity, Stephen Krashen's Monitor Model acknowledges the importance of both subconscious acquisition and overt application of rules of grammar. Moreover, subsequent theories, techniques, and methods such as Community Language Learning (Curran) and processing instruction (VanPatten) have continued to either emphasize or de-emphasize the importance of grammar in the second classroom. In addition, contemporary topics such as communicative (Savignon) and proficiency (Buck, Byrnes, and Thompson) have redefined second instruction without offering definite framework in which to place in-class grammar. The issues of whether to teach grammar and how it should be taught lie at the heart of the implicit-versus-explicit controversy. Indeed, teachers have taught grammar in variety of ways-inductively and deductively, in the native and in the target language, with explanations and without, in paradigms and in dialo ues (Garrett 134). Nevertheless, the most basic form of the grammar question has been: should grammar be taught inductively (implicitly) or deductively (explicitly) (Ellis; Garrett; Heilenman; McLaughlin; Terrell)? Barry McLaughlin refers to explicit and implicit instruction as controversial constructs in foreign theoretical study (129). More specifically, Harris Winitz describes explicit instruction of grammatical structures as a learning process in which the rules of the grammar of L2 are learned as formal statements [and in which] lexical understanding, in the beginning stages of instruction, is provided through the translation of words and phrases from the first language (34). Implicit grammatical instruction is one that exposes the learner to grammatical and lexical principles through natural experience (Asher; Krashen; Winitz). In addition to general division among researchers and methodologists, teachers are also split into two camps, those who believe that classroom learners will develop all the grammatical competence they need from exposure to appropriate input ... and those who insist that some explicit discussion of structure is necessary (Garrett 134). However, in spite of sharing goal of producing highly proficient second learner, implicit and explicit strategies diverge in al ost all areas of practice. In order to demonstrate the superiority of one approach over the other, many researchers have engaged in implicit-versus-explicit studies of in-

Default Reasoning and Generics

There are numerous logical formalisms capable of drawing conclusions using default rules. Such systems, however, do not normally determine where the default rules come from; i.e., what it is that makes Birds flya good rule, but Birds drive trucksa bad one.Generic sentences such as Birds fly are often used informally to describe default rules. I propose to take this characterization seriously, and claim that a default rule is adequate if the corresponding generic sentence is true. Thus, if we know that Tweety is a bird, we may conclude by default that Tweety flies, just in case Birds fly is a true sentence.In this paper, a quantificational account of the semantics of generic sentences is presented. It is argued that a generic sentence is evaluated not in isolation, but with respect to a set of relevant alternatives. For example, Mammals bear live young is true because among mammals that bear live young, lay eggs, undergo mitosis, or engage in some alternative form of procreation, the majority bear live young. Since male mammals do not procreate in any form, they do not count. Some properties of alternatives are presented, and their interactions with the phenomena of focus and presupposition is investigated.It is shown how this account of generics can be used to characterize adequate default reasoning systems, and several desirable properties of such systems are proved. The problems of the automatic acquisition of rules from natural language are discussed. Because rules are often explicitly expressed as generics, it is argued that the interpretation of generic sentences plays a crucial role in this endeavor, and it is shown how the theory presented here can facilitate such interpretation.

Genetic Tuning of a Fuzzy Controller

Abstract In a fuzzy controller, the rules derived from experts and the parameters of a membership function which correspond to a verbal word play an important role. The rule acquisition and the auto-tuning of membership parameters are one of prevalent research fields. In this paper, we propose a tuning method of the membership parameters for the fuzzy controller. The evaluation function of the fuzzy controller is well known as a very complex multi-peaked one against these membership parameters. The auto tuning method proposed here employs genetic algorithm in order to search for optimum solution which avoids falling in local optimum. The effectiveness and efficiency of the proposed method are ensured using a simulated example.

An Adaptive Hybrid Fuzzy - Neural Controller

This paper presents investigations toward adaptive fuzzy control using neural networks for the control of nonlinear and time variable physical processes. By using a hybrid structure, the fuzzy logic controller can be composed of its traditional components and two neural networks. The first neural network works as an adaptive rule estimator for online acquisition and modification of the fuzzy rules as it was presented in a previous work. Here a second neural network is proposed as a further development of the hybrid structure which implements the defuzzification function and works as an adaptive neural defuzzifier. The standard one step gradient descent learning procedure is implemented and the output from a conventional feedback controller is used for tuning the parameters of the neural defuzzifier. Comparison with the traditional fuzzy technique is discussed. The results obtained by simulation show the better performance of the proposed hybrid control structure.

Statistical Test of the Rule Assessment Methodology by Latent Class Analysis

A problem of Siegler's (1981) rule assessment methodology is that the assignment of subjects to rules takes place by an arbitrary criterion. This problem can be solved by latent class analysis by which we can test statistically how many rules are needed to fit the data and which these rules are. Two data sets of the balance scale test are analyzed. The first empirical data set stems from a study of Van Maanen, Been & Sijtsma (1989) and consists of 484 subjects in Grade 7 and Grade 8. The second data set is derived from the simulation of the PDP model of McClelland (1989). According to McClelland and Jenkins (1991), this connectionistic model simulates the saltatory acquisition of rules for tasks like the balance scale. The fit of the latent class models to the empirical data shows that rules can be found, that some are different from the ones Siegler proposes, that the correct rule is not acquired by the subjects in this sample, and that the rules in the transitional period are difficult to identify. The latent class models do not fit the PDP data, indicating that the behavior of the PDP model can not be characterized by rules.

Constrained Information Maximization to Control Internal Representatio

In the present paper, we propose a constrained information maximization method to control internal representations obtained in a course of learning. We focus upon hidden units and define information in hidden units acquired by learning. Internal representations are transformed by controlling this information. To control internal representations, a constraint is introduced in information maximization that total output from all the hidden units is a constant. By changing values of the constant, it is possible to generate many kinds of different internal representations, corresponding to the information content in hidden units. For example, we can obtain compact output patterns and specialized patterns of hidden units by changing the constant. We applied the constrained information maximization method to alphabet character recognition problems and a rule acquisition problem of an artificial language close to English. In the experiments, we were especially concerned with the generation of specialized hidden units, one of the typical example of the control of internal representations. Experimental results confirmed that we can control internal representations to produce specialized hidden units and to detect and extract main features of input patterns

Consciência sintática, consciência fonológica e aquisição de regras ortográficas

Vários estudos têm demonstrado uma estreita conexão entre o desenvolvimento da consciência fonológica e o domínio de escritas alfabéticas. Sabemos, entretanto, que estes sistemas de escrita não são fiéis à sua base fonológica e que para dominar a ortografia é preciso conscientizar-se de outros níveis de estruturação da língua. Estudo recente, com crianças inglesas, sugerem que o desenvolvimento da consciência sintática facilita a aquisição de regras ortográficas que envolvem análises morfo-sintáticas. O presente estudo investigou estas relações em 46 crianças brasileiras de classe-média baixa. As crianças foram avaliadas quanto ao desenvolvimento da consciência metalingüística no início da primeira série e quanto à aquisição da ortografia no final da primeira e da segunda séries. Os resultados indicaram que a consciência sintática é um facilitador específico da aquisição de regras ortográficas que envolvem análises morfo-sintáticas, enquanto que a consciência fonológica contribui principalmente para a aquisição de regras de contexto grafo-fônico.

Analogical transfer is effective in a serial reaction time task in Parkinson's disease: Evidence for a dissociable form of sequence learning

Several studies of procedural learning in Parkinson's disease (PD) have demonstrated that these patients are impaired with respect to age-matched control subjects. In order to examine more closely the specific impairment, we considered three dimensions along which a procedural learning task could vary. These are: (1) implicit vs explicit learning, (2) instance vs rule learning, and (3) learning with internal vs external error correction. We consider two hypotheses that could explain the impairments observed in PD for different types of explicit motor learning: (H1) an impairment related to the acquisition of rules vs specific instances, and (H2) an impairment in learning when no explicit error feedback is provided. In order to examine the condition of rule learning with external error feedback, we developed a modified version of the serial reaction time (SRT) protocol that tests analogical transfer in sequence learning (ATSL). Reaction times are measured for responses to visual stimuli that appear in several different repeating sequences. While these isomorphic sequences are different, they share a common rule. Verbatim learning of a sequence would result in negative transfer from one sequence to a different one, while rule learning would result in positive transfer. Parkinson's patients and age-matched controls demonstrate significant acquisition and positive transfer of the rule between sequences. Our results demonstrate that PD patients are capable of learning and transferring rule or schema-based representations in an explicit learning format, and that this form of learning may be functionally distinct from learning mechanisms that rely on representations of the verbatim or statistical structure of sequences.

Scheduling Rules Acquisition by Inductive Learning

Scheduling Rules Acquisition by Inductive Learning

Understanding teachers' evaluation criteria: A condition for success in science classes

This study is part of a broader research project. The main aim was to find out pedagogic practices which can improve students' science achievement, namely, in complex cognitive competencies. The study is based on Bernstein's theory. Previous studies have suggested that the explicitness of the criteria of evaluation is related to students' scientific understanding and achievement. One of the many ways in which the evaluation criteria can be made explicit to students is through assessment tests, and their correction and marking. In this study, we analyze the extent to which students understand teachers' evaluation criteria, more specifically, teachers' marking criteria and procedures (i.e., the extent to which they have recognition and realization rules to the assessing context). We also analyze the relation of that understanding with social class, social context of the school, teacher's conceptual demand, teachers' explicitness of criteria, and science achievement. A clear relation between students' acquisition of recognition and realization rules and social class is shown: the higher the social class, the higher that acquisition. A privileged school's social context and the teacher's explicitness of assessing criteria also contribute to students' understanding of teachers' evaluation criteria. This understanding influences science achievement, especially in complex competencies. © 1996 John Wiley & Sons, Inc.

Unsupervised learning of part-of-speech guessing rules

Words unknown to the lexicon present a substantial problem to part-of-speech tagging. In this paper we present a technique for fully unsupervised acquisition of rules which guess possible parts of speech for unknown words. This technique does not require specially prepared training data, and uses instead the lexicon supplied with a tagger and word frequencies collected from a raw corpus. Three complimentary sets of word-guessing rules are statistically induced: prefix morphological rules, suffix morphological rules and ending guessing rules. The acquisition process is strongly associated with guessing-rule evaluation methodology which is solely dedicated to the performance of part-of-speech guessers. Using the proposed technique a guessing-rule induction experiment was performed on the Brown Corpus data and rule-sets, with a highly competitive performance, were produced and compared with the state-of-the-art. To evaluate the impact of the word-guessing component on the overall tagging performance, it was integrated into a stochastic and a rule-based tagger and applied to texts with unknown words.