v. 1. Tan suo zhe dao lu de tan suo -- v. 2. Lukaqi yu Makesi -- v. 3. Makesi zhu yi zhe xue ji ben wen ti yan jiu -- v. 4. Makesi zhu yi zhe xue jing dian wen xian yan jiu.
v.1. zhe xue de mu guang -- v.2. shu ren de shi jie -- v.3. tan suo zhen shan mei -- v.4. chong gao de wei zhi -- v.5. zhe xue guan yan jiu -- v.6-7. bian zheng fa yan jiu -- v.8-9. zhe xue tong lun.
Implicit processes are thought to be relatively fast, inaccessible, holistic, and imprecise, while explicit processes are slow, accessible and precise (e.g., Reber, 1989, Sun 2002). This dichotomy is closely related to some other well-known dichotomies including symbolic versus subsymbolic processing (Rumelhart et al., 1986), conceptual versus subconceptual processing (Smolensky, 1988), and conscious versus unconscious processing (Jacoby et al., 1994). This dichotomy has been justified by extensive studies of implicit and explicit learning, implicit and explicit memory, and implicit versus explicit metacognition (...) (Reder, 1996). (shrink)
As we know, a cognitive architecture is a domain-generic computational cognitive model that may be used for a broad analysis of cognition and behavior. Cognitive architectures embody theories of cognition in computer algorithms and programs. Social simulation with multi-agent systems can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents (as argued in Sun 2001). In this survey, an example cognitive architecture will be given, and its application to social simulation will be sketched.
Implicit processes are thought to be relatively fast, inaccessible, holistic, and imprecise, while explicit processes are slow, accessible and precise (e.g., Reber, 1989, Sun 2002). This dichotomy is closely related to some other wellknown dichotomies including symbolic versus subsymbolic processing (Rumelhart et al., 1986), conceptual versus subconceptual processing (Smolensky, 1988), and conscious versus unconscious processing (Jacoby et al., 1994). This dichotomy has been justified by extensive studies of implicit and explicit learning, implicit and explicit memory, and implicit versus explicit metacognition (...) (Reder, 1996). (shrink)
In developing autonomous agents, one usually emphasizes only (situated) procedural knowledge, ignoring more explicit declarative knowledge. On the other hand, in developing symbolic reasoning models, one usually emphasizes only declarative knowledge, ignoring procedural knowledge. In contrast, we have developed a learning model Clarion, which is a hybrid connectionist model consisting of both localist and distributed representations, based on the two-level approach proposed in Sun (1995). learns and utilizes both procedural and declarative knowledge, tapping into the synergy of..
This paper explicates the interaction between the implicit and explicit learning processes in skill acquisition, contrary to the common tendency in the literature of studying each type of learning in isolation. It highlights the interaction between the two types of processes and its various effects on learning, including the synergy effect. This work advocates an integrated model of skill learning that takes into account both implicit and explicit processes; moreover, it embodies a bottom-up approach (first learning implicit knowledge and then (...) explicit knowledge on its basis) towards skill learning. The paper shows that this approach accounts for various effects in the process control task data, in addition to accounting for other data reported elsewhere. (shrink)
Finance ethics have drawn increasing attention from both government regulators and academic researchers. This paper addresses the issue of insider trading ethics. Previous studies on insider trading ethics have failed to provide convincing arguments and consistent results. In particular, the arguments against insider trading are based primarily on moral and philosophical grounds and lack empirical rigor. This study intends to establish and examine the relationship between the ethical issue and economic issue of insider trading. We argue that the ethics of (...) insider trading is in essence an economic rather than a moral issue. It is so far not clear to what extent insider trading may increase or decrease shareholders wealth. Until then, we must take care to avoid over-regulating insider trading. (shrink)
In this essay, I examine the nature of Chinese logic and Chinese sciences in the history of China. I conclude that Chinese logic is essentially analogical, and that the Chinese did not have theoretical sciences. I then connect these together and explain why the Chinese failed to develop theoretical sciences, even though they enjoyed an advanced civilization and great scientific and technological innovations. This is because a deductive system of logic is necessary for the development of theoretical sciences, and analogical (...) logic cannot provide the deductive connections between a theory and empirical observations required by a theoretical science. This also offers a more satisfactory answer to the long-standing Needham Problem. (shrink)
Symbols should be grounded, as has been argued before. But we insist that they should be grounded not only in subsymbolic activities, but also in the interaction between the agent and the world. The point is that concepts are not formed in isolation (from the world), in abstraction, or "objectively." They are formed in relation to the experience of agents, through their perceptual/motor apparatuses, in their world and linked to their goals and actions. This paper takes a detailed look at (...) this relatively old issue, with a new perspective, aided by our work of computational cognitive model development. To further our understanding, we also go back in time to link up with earlier philosophical theories related to this issue. The result is an account that extends from computational mechanisms to philosophical abstractions. (shrink)
“The Strong Programme” is put forward as a metaphysical theory of sociology by the Edinburgh School (SSK) to study the social causes of knowledge. Barry Barnes and David Bloor are the proponents of the School. They call their programme “the Relativist View of Knowledge” and argue against rationalism in the philosophy of science. Does their relativist account of knowledge present a serious challenge to rationalism, which has dominated 20th century philosophy of science? I attempt to answer this question by criticizing (...) the main ideas of SSK and defending rationalism theories in modern philosophy of science. (shrink)
The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among entities at a high (...) level can be reduced to causal relationships among simpler entities at a more detailed level. We argue that a similar hierarchy makes possible an equally productive approach toward cognitive modeling. The levels of models that we conceive in relation to cognition include, at the highest level, sociological/anthropological models of collective human behavior, behavioral models of individual performance, cognitive models involving detailed mechanisms, representations, and processes, as well as biological/physiological models of neural circuits, brain regions, and other detailed biological processes. (shrink)
This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and explicit processes in most (...) tasks, (c) the redundant representation of explicit and implicit knowledge, (d) the integration of the results of explicit and implicit processing, and (e) the iterative (and possibly bidirectional) processing. A computational implementation of the theory is developed based on the CLARION cognitive architecture and applied to the simulation of relevant human data. This work represents an initial step in the development of process-based theories of creativity encompassing incubation, insight, and various other related.. (shrink)
This paper explores the interaction between implicit and explicit processes during skill learning, in terms of top-down learning (that is, learning that goes from explicit to implicit knowledge) versus bottom-up learning (that is, learning that goes from implicit to explicit knowledge). Instead of studying each type of knowledge (implicit or explicit) in isolation, we stress the interaction between the two types, especially in terms of one type giving rise to the other, and its effects on learning. The work presents an (...) integrated model of skill learning that takes into account both implicit and explicit processes and both top-down and bottom-up learning. We examine and simulate human data in the Tower of Hanoi task. The paper shows how the quantitative data in this task may be captured using either top-down or bottom-up approaches, although top-down learning is a more apt explanation of the human data currently available. These results illustrate the two different directions of learning (top-down versus bottom-up), and thereby provide a new perspective on skill learning. Ó 2003 Elsevier B.V. All rights reserved. (shrink)
The goal of this research is to understand the interaction of implicit and explicit psychological processes in dealing with emotional distractions and meta-cognitive control of such distractions. The questions are how emotional and meta-cognitive processes can be separated into implicit and explicit components, and how such a separation can be utilized to improve self-regulation of emotion, which can have significant theoretical and practical implications.
Research in computational cognitive modeling investigates the nature of cognition through developing process-based understanding by specifying computational models of mechanisms (including representations) and processes. In this enterprise, a cognitive architecture is a domaingeneric computational cognitive model that may be used for a broad, multiple-level, multipledomain analysis of behavior. It embodies generic descriptions of cognition in computer algorithms and programs. Developing cognitive architectures is a difficult but important task. In this article, discussions of issues and challenges in developing cognitive architectures will (...) be undertaken, and an example cognitive architecture (CLARION) will be described. (shrink)
Assumed benefits from improved reputation are often used as motives to drive corporate social responsibility (CSR) initiatives. Are improved cost efficiencies among these reputation benefits? Cost efficiencies and cost management have become more relevant as revenue streams dry up in these tough economic times. Can a good reputation aid these efforts to develop cost efficiencies specifically when managing labor costs? Prior research hypothesizes that good reputation can create labor productivity and efficiency benefits. The purpose of this study is to empirically (...) investigate reputation’s relationship with labor efficiency, labor productivity, and labor cost. Using a sample of highly reputable firms from Fortun e’s America’s Most Admired Companies list and a corresponding matched sample of firms, we find that reputation is associated with improved labor efficiency and labor productivity. However, we do not find a significant association between reputation and reduced labor costs. Our study contributes to current research hypothesizing and finding efficiency benefits associated with good reputation. Documenting these potential reputation benefits has important implications for CSR activities and initiatives. It supports recent work that incorporates reputation into a more developed model of the relationship between CSR and performance (Vilanova et al.: 2009 , Journal of Business Ethics 87 , 57–69). This work is useful to businesses and supports strategies focused on “doing well by doing good” and maintaining healthy reputations. (shrink)
This study investigates the complexities in the relationship between perceptions of organizational politics and performance ratings by examining the moderating effect of impression management on that relationship. Expectancy theory was employed to better understand the moderating effect. We proposed that two kinds of impression management tactics occurred: supervisor-focused and job-focused, respectively. It was hypothesized that increased exercise of impression management would mitigate the negative effects of perceptions of organizational politics and performance ratings. Data were collected from 290 full-time employees of (...) ten state-owned enterprises in Taiwan. Hierarchical moderated regression analysis of data revealed that the job-focused tactics exerted a significant moderating effect on the relationship between perceptions of organizational politics and performance ratings. When perceptions of organizational politics are low, employees who engage in high levels of job-focused impression management tactics are more likely to gain better ratings than those who employ low-level tactics. (shrink)
Most psychological theories of problem solving have focused on modeling explicit processes that gradually bring the solver closer to the solution in a mostly explicit and deliberative way. This approach to problem solving is typically inefficient when the problem is too complex, ill-understood, or ambiguous. In such a case, a ‘creative’ approach to problem solving might be more appropriate. In the present paper, we propose a computational psychological model implementing the Explicit-Implicit Interaction theory of creative problem solving that involves integrating (...) the results of implicit and explicit processing. In this paper, the new model is used to simulate insight in creative problem solving and the overshadowing effect. (shrink)
We believe that the distinction between procedural and declarative knowledge unnecessarily confounds two issues: action-centeredness and accessibility, and can be made clearer through separating the two aspects. The work presents an integrated model of skill learning that takes into account both implicit and explicit processes and both action-centered and non-action-centered knowledge. We examine and simulate human data in the Letter Counting task. The work shows how the data may be captured using either the action-centered knowledge alone or the combined action-centered (...) and non-action-centered knowledge. The results provide a new perspective on skill learning. (shrink)
In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...) of consciousness. The causal relationships implicit in definitions of access consciousness and phe- nomenal consciousness are made explicit, and the corresponding causal relationships at the more detailed levels of perception, memory, and skill learning described. Extension of these causal relationships to physiological and neural levels is discussed. The general capability of a range of current consciousness models to support a modular hierarchy which could generate these causal relationships is reviewed, and the specific capabilities of two models with good general capabilities are compared in some detail. Ó 2003 Elsevier Inc. All rights reserved. (shrink)
What is computational cognitive modeling? What exactly can it contribute to cognitive science? What has it contributed thus far? Where is it going? Answering such questions may sound overly defensive to the insiders of computational cognitive modeling, and may even seem so to some other cognitive scientists, but they are very much needed in a volume like this—because they lie at the very foundation of this field. Many insiders and outsiders alike would like to take a balanced and rational look (...) at these questions, without indulging in excessive cheer-leading, which, as one would expect, happens sometimes amongst computational modeling enthusiasts. (shrink)
China has long enjoyed its position as the world’s cheapest production country. However, this position is being shaken due to the increasingly rising costs in China in pace with China’s rapid economic development. China’s New Labour Contract Law which took effect from 1 January 2008 has further pushed the labour costs in China in general. The purpose of this article is to arrive at an in-depth understanding of why foreign firms conduct sourcing in China where sourcing is becoming increasingly expensive. (...) The experiences of four Swedish companies in the textile and clothing industry (TCI) conducting sourcing in China are presented. Our findings show that sourcing in China is becoming both cost- and strategy-driven. Companies purely chasing the cheapest production would most probably consider leaving China, whereas companies with a long-term strategic intent and a high level of business ethics and corporate social responsibility (CSR) practices will retain all or most of their sourcing activities on the Chinese soil despite the rising costs. (shrink)
This article addresses issues in developing cognitive architectures--generic computational models of cognition. Cognitive architectures are believed to be essential in advancing understanding of the mind, and therefore, developing cognitive architectures is an extremely important enterprise in cognitive science. The article proposes a set of essential desiderata for developing cognitive architectures. It then moves on to discuss in detail some of these desiderata and their associated concepts and ideas relevant to developing better cognitive architectures. It argues for the importance of taking (...) into full consideration these desiderata in developing future architectures that are more cognitively and ecologically realistic. A brief and preliminary evaluation of existing cognitive architectures is attempted on the basis of these ideas. (shrink)
This paper explores an approach for autonomous generation of symbolic representations from an agent's subsymbolic activities within the agent-environment interaction. The paper describes a psychologically plausible general framework and its various methods for autonomously creating symbolic representations. The symbol generation is accomplished within, and is intrinsic to, a generic and comprehensive cognitive architecture for capturing a wide variety of psychological processes (namely, CLARION). This work points to ways of obtaining more psychologically/cognitively realistic symbolic and subsymbolic representations within the framework of (...) a cognitive architecture, and accentuates the relevance of such an approach to cognitive science and psychology. (shrink)
Agent-based social simulation (with multi-agent systems), which is an important aspect of social computing, can benefit from incorporating cognitive architectures, as they provide a realistic basis for modeling individual agents and therefore their social interactions. A cognitive architecture is a domain-generic computational cognitive model that may be used for a broad multiple-domain analysis of individual behavior. In this article, an example of a cognitive architecture is given, and its applications to social simulation described. Some challenging issues in this regard are (...) outlined. (shrink)
This paper describes how meta-cognitive processes (i.e., the self monitoring and regulating of cognitive processes) may be captured within a cognitive architecture Clarion. Some currently popular cognitive architectures lack sufficiently complex built-in meta-cognitive mechanisms. However, a sufficiently complex meta-cognitive mechanism is important, in that it is an essential part of cognition and without it, human cognition may not function properly. We contend that such a meta-cognitive mechanism should be an integral part of a cognitive architecture. Thus such a mechanism has (...) been developed within the Clarion cognitive architecture. The paper demonstrates how human data of two meta-cognitive experiments are simulated using Clarion. The simulations show that the meta-cognitive processes represented by the experimental data (and beyond) can be adequately captured within the Clarion framework. (shrink)
This article explicates the interaction between implicit and explicit processes in skill learning, in contrast to the tendency of researchers to study each type in isolation. It highlights various effects of the interaction on learning (including synergy effects). The authors argue for an integrated model of skill learning that takes into account both implicit and explicit processes. Moreover, they argue for a bottom-up approach (first learning implicit knowledge and then explicit knowledge) in the integrated model. A variety of qualitative data (...) can be accounted for by the approach. A computational model, CLARION, is then used to simulate a range of quantitative data. The results demonstrate the plausibility of the model, which provides a new perspective on skill learning. (shrink)
In attempting to explain or deal with negative workplace behaviours such as workplace bullying, the notion of ‘workplace psychopaths’ has recently received much attention. Focusing on individual aspects of negative workplace behaviour is at odds with more systemic approaches that recognise the contribution of individual, organisational and societal influences, without seeking to blame a person(s) for their behaviour or personality disorder. Regarding a coworker as a psychopath is highly stigmatising, and given the relatively low prevalence of psychopathy in the community, (...) is likely to be incorrect. Sources promoting the notion of workplace psychopathy provide lists of diagnostic criteria and appear to encourage the perception that it is common. This research examines how lay persons use behavioural criteria consistent with psychopathy and the label ‘psychopath’ in relation to a coworker. 307 Australian workers completed an online survey concerning their experience of workplace bullying, which also asked them to rate a coworker’s behaviour on a range of scales to assess perceptions of psychopathy. Rates of psychopathy, when using labels and behavioural criteria, were found to be much higher than scientific estimates of prevalence, for both participants who had been bullied and those who had not. A higher proportion of non-bullied participants classified a coworker as a psychopath when using the label ‘psychopath’, compared to when using behavioural criteria. The notion that there are psychopaths in every workplace should be treated with caution to ensure that the potential for ‘misdiagnosis’ and stigmatisation do not cause further harm in situations of unacceptable workplace behaviours. (shrink)
In this paper, we introduce a variety bdO of Ockham algebras with balanced double pseudocomplementation, consisting of those algebras of type where is an Ockham algebra, is a double p -algebra, and the operations and are linked by the identities [ f ( x )]* = [ f ( x )] + = f 2 ( x ), f ( x *) = x ** and f ( x + ) = x ++ . We give a description of the (...) congruences on the algebras, and show that there are precisely nine non-isomorphic subdirectly irreducible members in the class of the algebras via the Priestley duality. We also describe all axioms in the variety bdO , and provide a characterization of all subvarieties of bdO determined by 12 none-equivalent axioms, identifying therein the biggest subvariety in which every principal congruence is complemented. (shrink)
The present issue is the beginning of a new journal from various sub-disciplines and paradigms in order – Cognitive Systems Research – which we have to construct a coherent picture of how the various developed in response to what we perceive to be an pieces fit together overall. Such a synthesis is unfilled niche in the current literature in the areas of essential to the discovery of designs for general Cognitive Science and Artificial Intelligence.
Sequential behavior is essential to intelligence, and it is a fundamental part of human activities ranging from reasoning to language, and from everyday skills to complex problem solving. In particular, sequence learning is an important component of learning in many task domains — planning, reasoning, robotics, natural language processing, speech recognition, adaptive control, time series prediction, financial engineering, DNA sequencing, and so on. Naturally, there are many different approaches towards sequence learning, resulting from different perspectives taken in different task domains. (...) These approaches deal with somewhat differently formulated sequential learning problems (for example, some with actions and some without), and/ or different aspects of sequence learning (for example, sequence prediction vs. sequence recognition). Sequence learning is clearly a difiicult task. More powerful algorithms for sequence learning are needed in all of these afore-mentioned domains. It is our view that the right approach to develop better techniques, algorithms, models. (shrink)
_role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approxi-_ _mate characteristics of human consciousness. In doing so, the paper examines explicit and implicit learning in a variety_ _of psychological experiments and delineates the conscious/unconscious distinction in terms of the two types of learning_ _and their respective products. The distinctions are captured in a two-level action-based model C_larion_. Some funda-_ _mental theoretical issues are also clari?ed with the help of the model. Comparisons with (...) existing models of conscious-_. (shrink)
This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Computational models provide both conceptual clarity and precision at the same time. This book substantiates this approach through overviews and many (...) examples. (shrink)
Recent scandals at Enron, WorldCom and Global Crossing have put the ethical spotlight on corporate malfeasance as never before. However, these are the situations in which management knew that they made the wrong choice. As professor Joseph Badaracco of Harvard Business School points out, the real ethical dilemmas arise when people must choose between right and right — where both choices can be justified, yet one must be chosen over the other. Whether or not to reprice stock options represents one (...) such ethical dilemma. Repricing can help exodus of talented employees and motivate them to improve firm performance. However, it alienates shareholders and other workers of the company who are left unprotected from the adverse economic consequences of a stock price decline.In this paper we examine the ethics and the economics of stock option repricing. We find that repricing runs counter to two key tenets of business ethics — distributive justice and ordinary decency. To examine the economics of repricing, we draw upon agency theory to identify situations where repricing has the potential to benefit shareholders. However, a survey of empirical research reveals that these benefits do not translate into reality. Repricing does not improve employee retention or firm performance. In addition, managers benefit by opportunistically timing the repricing. Due to weaknesses in corporate governance such as lack of independence and conflicts of interest, the current repricing practice seems to be at odds with the objective of shareholder wealth maximization, and at a more fundamental level, a violation of board's fiduciary duty to shareholders. We offer suggestions that mitigate the ethically undesirable effects of repricing in the wider context of prevailing corporate governance and regulatory environment. We believe that these suggestions, if properly implemented, can transform repricing from a greed-inspired evil to a valuable compensation tool to retain employees, boost their morale, and enhance stockholder wealth. (shrink)
We present a skill learning model CLARION. Different from existing models of high-level skill learning that use a topdown approach (that is, turning declarative knowledge into procedural knowledge), we adopt a bottom-up approach toward low-level skill learning, where procedural knowledge develops first and declarative knowledge develops later. CLAR- ION is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line learning. We compare the model with human data in a minefield navigation task. A match between the model and (...) human data is found in several respects. (shrink)
Although computational models of cognitive agents that incorporate a wide range of cognitive functionalities have been developed in cognitive science, most of the work in social simulation still assumes rudimentary cognition on the part of the agents. In contrast, in this work, the interaction of cognition and social structures/processes is explored, through simulating survival strategies of tribal societies. The results of the simulation demonstrate interactions between cognitive and social factors. For example, we show that cognitive capabilities and tendencies may be (...) relevant to what social institutions may be adopted. This work points to a cognitively based approach towards social simulation, as well as a new area of researchâexploring the cognitiveâsocial interaction through cognitively based social simulation. (shrink)
Do participants bring their own priors to an experiment? If so, do they share the same priors as the researchers who design the experiment? In this article, we examine the extent to which self-generated priors conform to experimenters’ expectations by explicitly asking participants to indicate their own priors in estimating the probability of a variety of events. We find in Study 1 that despite being instructed to follow a uniform distribution, participants appear to have used their own priors, which deviated (...) from the given instructions. Using subjects’ own priors allows us to account better for their responses rather than merely to test the accuracy of their estimates. Implications for the study of judgment and decision making are discussed. (shrink)
This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...) functional role of consciousness, in the form of the synergy between the conscious and the unconscious. The fit between the model and various cognitive phenomena and data (documented in the psychological literatures) is discussed to accentuate the plausibility of the model and its explanation of consciousness. Comparisons with existing models of consciousness are made in the end. (shrink)
Recent corporate disgraces and corruption have heightened concerns about ethically questionable behavior in business. The construct of ethically questionable behavior is an under-portrayed area of management field research, and deserves further studying, especially in sales positions. This study uses four variables from the human resource management field to explain the ethically questionable behavior of sales representatives in the pharmaceutical industry. These variables include frame pattern, commission structure, behavior control type, and marketing norm perceptions. This work uses a 2*2*2*2 subject experimental (...) design, and 328 fully completed questionnaires for logistic regression analysis. Results suggest that a medical representative in a loss frame (compared with a gain frame), in a high commission structure (compared with a low commission structure), in loose behavior control (compared with strict behavior control), and in a low perception of marketing norm (compared with a high perception of marketing norm), is more likely affected by heuristic biases and make an ethically questionable choice. (shrink)
This paper discusses the topics, goals, values and methods of Chinese logic. It holds that the goal of the research in Chinese logic is to reveal its structure, content, rules, and essential character, as well as to reveal both similarities and differences between Chinese and foreign logic. The value of the research is to carry forward and develop the outstanding heritage of Chinese logic. Its method is to annotate original works of Chinese ancient logic with the tools of modern language (...) and logic in order to reveal both the particular nature and the universal qualities of Chinese logic. The method also explores the differences and similarities between Chinese and foreign logic. In recent years, research in Chinese logic has developed considerably; it has also logged many important achievements. But there are many different views about the complexity and long-term goals of the research. Future research will build on the merits of different kinds of logic, promote Chinese logic, and increase communication between Chinese logic and foreign logic. (shrink)
This paper explores cognitively realistic social simulations by deploying the CLARION cognitive architecture in a simple organizational simulation, which involves the interaction of multiple cognitive agents. It argues for an integration of the two separate strands of research: cognitive modeling and social simulation. Such an integration could, on the one hand, enhance the accuracy of social simulation models by taking into full account the effects of individual cognitive factors, and on the other hand, it could lead to greater explanatory, predictive, (...) and prescriptive power from these models. (shrink)
In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...) of consciousness. The causal relationships implicit in definitions of access consciousness and phe- nomenal consciousness are made explicit, and the corresponding causal relationships at the more detailed levels of perception, memory, and skill learning described. Extension of these causal relationships to physiological and neural levels is discussed. The general capability of a range of current consciousness models to support a modular hierarchy which could generate these causal relationships is reviewed, and the specific capabilities of two models with good general capabilities are compared in some detail. Ó 2003 Elsevier Inc. All rights reserved. (shrink)
The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule- based reasoning and whether they involve distributed or localist representations. The bene®ts and disadvantages of different representations and systems are outlined, and conclusions drawn regarding the capabilities of connectionist inference systems when compared with symbolic inference systems or when used (...) for cognitive modelling. q 2001 Elsevier Science Ltd. All rights reserved. (shrink)
The paper attempts to account for common pattems in commonsense reasoning through integrating rule-based reasoning and similarity-based reasoning as embodied in connectionist models.
This paper introduces a hybrid model that unifies connectionist, symbolic, and reinforcement learning into an integrated architecture for bottom-up skill learning in reactive sequential decision tasks. The model is designed for an agent to learn continuously from on-going experience in the world, without the use of preconceived concepts and knowledge. Both procedural skills and high-level knowledge are acquired through an agent’s experience interacting with the world. Computational experiments with the model in two domains are reported.
In the current research on multi-agent systems (MAS), many theoretical issues related to sociocultural processes have been touched upon. These issues are in fact intellectually profound and should prove to be significant for MAS. Moreover, these issues should have equally significant impact on cognitive science, if we ever try to understand cognition in the broad context of sociocultural environments in which cognitive agents exist. Furthermore, cognitive models as studied in cognitive science can help us in a substantial way to better (...) probe multi-agent issues, by taking into account essential characteristics of cognitive agents and their various capacities. In this paper, we systematically examine the interplay among social sciences, MAS, and cognitive science. We try to justify an integrated approach for MAS which incorporates different perspectives. We show how a new cognitive model, CLARION, can embody such an integrated approach through a combination of autonomous learning and assimilation. (shrink)
During the two days of the workshop, various presentations and discussions brought to light many new ideas, controv ersies, and syntheses. The fo cus was on learning and architecture s that feature hybrid representations and supp ort hybrid learning. It was a general consensus among the workshop participants that hybrid connectionist-symb olic mo dels constitute a promising aven ue toward developing more robust, more p owerful, and more versatile architecture s b oth for cognitive mo deling and for intelligen t (...) systems. The need for such mo dels has b een slowly but steadily growing over the past 5 years. Some new, imp ortant approaches have b een prop osed and develop ed, some of which were presented at the workshop. worthwhil e further pursuing In sum. (shrink)
Most of the work in agent-based social simulation has assumed highly simplified agent models, with little attention being paid to the details of individual cognition. Here, in an effort to counteract that trend, we substitute a realistic cognitive agent model (CLARION) for the simpler models previously used in an organizational design task. On that basis, an exploration is made of the interaction between the cognitive parameters that govern individual agents, the placement of agents in different organizational structures, and the performance (...) of the organization. It is suggested that the two disciplines, cognitive modeling and social simulation, which have so far been pursued in relative isolation from each other, can be profitably integrated. (shrink)
A pO -algebra $${(L; f, \, ^{\star})}$$ is an algebra in which ( L ; f ) is an Ockham algebra, $${(L; \, ^{\star})}$$ is a p -algebra, and the unary operations f and $${^{\star}}$$ commute. Here we consider the endomorphism monoid of such an algebra. If $${(L; f, \, ^{\star})}$$ is a subdirectly irreducible pK 1,1 - algebra then every endomorphism $${\vartheta}$$ is a monomorphism or $${\vartheta^3 = \vartheta}$$ . When L is finite the endomorphism monoid of L is (...) regular, and we determine precisely when it is a Clifford monoid. (shrink)
The current debate on corporate governance has been "polarised" between, on the one hand, the shareholding paradigm and, on the other hand, the stakeholding paradigm. However, underpinning the main theories are hidden paradoxical assumptions that lead to concerns over the credibility and validity of this dichotomised approach. Both camps of the debate rely on a homeostatic and entitative conception of the corporation and its governance structures. Both camps suffer from an inadequate attention to the underlying philosophical presuppositions in which the (...) static approach is rooted. To avoid the traditional trap in theorising, an alternative processual approach is proposed for a better understanding of the inherent overflow and heterogeneity of corporate governance practice. (shrink)
Abstra,ct— This paper will discuss learning in hybrid models that goes beyond simple rule extraction from backpropagation networks. Although simple rule extraction has received a lot of research attention, to further develop hybrid learning models that include both symbolic and subsymbolic knowledge and that learn autonomously, it is necessary to study autonomous learning of both subsymbolic and symbolic knowledge in integrated architectures. This paper will describe knowledge extraction from neural reinforcement learning. It includes two approaches towards extracting plan knowledge: the (...) extraction of explicit, symbolic rules from neural reinforcement learning, and the extraction of complete plans. This work points to the creation of a general framework for achieving the subsymbolic to symbolic transition in an integrated autonomous learning framework. (shrink)
To explore the development of contemporary Chinese philosophy, fundamentally, is to explore the development of Marxist philosophy in contemporary China. The disputes over philosophical views in Chinese academic circles during the first half of the twentieth century have been focused on understanding Marxist philosophy from such aspects as “what kind of philosophy Chinese society needs,” “the relation of philosophy to science,” and “philosophy as an idea to reflect on one’s life.” These explorations have provided us a significant ideological insight into (...) the development of Marxist philosophy and contemporary Chinese philosophy; that is, in contemporary China, Marxist philosophy, as a doctrine of the liberation and all-round development of human beings, exists not only as a kind of “doctrine” or “academy” but also as a kind of widely accepted “xueyuan (academic cultivations)” among people. (shrink)
This paper presents a GA-based multi-agent reinforce- ment learning bidding approach (GMARLB) for perform- ing multi-agent reinforcement learning. GMARLB inte- grates reinforcement learning, bidding and genetic algo- rithms. The general idea of our multi-agent systems is as follows: There are a number of individual agents in a team, each agent of the team has two modules: Q module and CQ module. Each agent can select actions to be performed at each step, which are done by the Q module. While the (...) CQ module determines at each step whether the agent should continue or relinquish control. Once an agent relinquishes its control, a new agent is selected by bidding algorithms. We applied GA-based GMARLB to the Backgammon game. The experimental results show GMARLB can achieve a su- perior level of performance in game-playing, outperforming PubEval, while the system uses zero built-in knowledge. (shrink)
traction from reinforcement learners It addresses two ap proaches towards knowledge extraction the extraction of ex plicit symbolic rules from neural reinforcement learners and the extraction of complete plans from such learners The advantages of such knowledge extraction include the improvement of learning especially with the rule extraction approach and the improvement of the usability of re sults of learning..
Zuphu Xi (1130â1200) was one of the most influential philosophers in the history of Chinese philosophy. From the beginning of the fourteenth century until 1905, when the examination system was abolished, his and Cupheng Yiâs interpretations of the Confucian Classics were regarded as orthodox and served as the basis of civil service examinations and intellectual standards for the Chinese literati. His influence was not limited to China, as his thoughts became orthodoxy in Korea and in some important schools of thought (...) in Japan (see Chan). Because of his great contribution to culture, Zuphu Xi has been honored as Zhuzi or Zuphu Fuzi. This paper will review contemporary Chinese studies of Zhuzi, particularly of his philosophy, that have been conducted in mainland China since 1980. (shrink)
An algebra A is said to be congruence coherent if every subalgebra of A that contains a class of some congruence on A is a union of -classes. This property has been investigated in several varieties of lattice-based algebras. These include, for example, de Morgan algebras, p-algebras, double p-algebras, and double MS-algebras. Here we determine precisely when the property holds in the class of symmetric extended de Morgan algebras.
The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous (...) simulations and to human data are obtained. It is found that while different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between our model and the constructivist view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights. (shrink)
This commentary examines one aspect of the target article – the comparison of ACT-R with connectionist models. It argues that conceptions of connectionist models should be broadened to cover the whole spectrum of work in this area, especially the so-called hybrid models. Doing so may change drastically ratings of connectionist models, and consequently shed more light on the developing field of cognitive architectures.
top-down approach (that is, turning declarative knowledge into procedural knowledge), we adopt a bottom-up approach toward lowlevel skill learning, where procedural knowledge develops rst and declarative knowledge develops from it. Clarionwhich follows this approach is formed by integrating connectionist, reinforcement, and symbolic learning methods to perform on-line learning. We compare the model with human data in a mine eld navigation task. A match between the model and human data is observed in several comparisons.
methods to improve reinforcement learning are identi ed and discussed in some detail Each demonstrates to some extent the advantages of combining RL and symbolic meth ods These methods point to the potentials and the chal lenges of this line of research..
chical reinforcement learning that does not rely on a pri ori hierarchical structures Thus the approach deals with a more di cult problem compared with existing work It in volves learning to segment sequences to create hierarchical structures based on reinforcement received during task ex ecution with di erent levels of control communicating with each other through sharing reinforcement estimates obtained by each others The algorithm segments sequences to re duce non Markovian temporal dependencies to facilitate the learning of the (...) overall task Initial experiments demon strated the basic promise of the approach.. (shrink)
