In order to usurp the Party, seize power and restore capitalism, the Wang-Chang-Chiang-Yao anti-Party clique has turned out counterrevolutionary opinions in the ideological realm. They have tried in every way to distort and revise history and have fabricated the "struggle between the Confucianists and the Legalists" in history. They have confounded different social contradictions and have replaced the class struggle with the "struggle between the Confucianists and the Legalists" and the antagonism within the landlord class with the "line struggle." To (...) them, Legalists were always "progressive" and "innovative" while Confucianists always "represented the forces of restoration." They have tried their best to glorify emperors, kings, generals and ministers in history, to praise Legalists as "saviors," to cover up the Legalists' nature as an exploiting class, to call for metaphysics and the idealist viewpoint of history, and to turn out revisionist fallacies. Because important changes took place in the Confucian and Legalist schools during the periods of the Western and Eastern Han dynasties, the "Gang of Four" and the writers in its service have showed a great interest in histories of the dynasties and have published a series of articles on the so-called "struggle between the Confucianists and the Legalists." In the current struggle against the "Gang of Four," it is of great practical significance to review the changes in the Confucian and Legalist schools and their roles and class nature during the Han dynasties, to criticize and expose the criminal clique's counterrevolutionary political intrigues and plots, and to clarify the historical facts confused by the "Gang of Four.". (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 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)
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..
Spotting the Sun: A translation and analysis of three early seventeenth-century works on sunspots Content Type Journal Article Category Essay Review Pages 1-6 DOI 10.1007/s11016-011-9598-1 Authors Luciano Boschiero, Campion College, PO Box 3052, Toongabbie East, NSW 2146, Australia Journal Metascience Online ISSN 1467-9981 Print ISSN 0815-0796.
The main purpose of this study is to explore and map the intellectual structure of business ethics studies during 1997–2006 by analyzing 85,000 cited references of 3,059 articles from three business ethics related journals in SSCI and SCI databases. In this article, co-citation analysis and social network analysis techniques are used to research intellectual structure of the business ethics literature. We are able to identify the important publications and the influential scholars as well as the correlations among these publications by (...) analyzing citation and co-citation. Three factors emerged in this study are: (1) ethical/unethical decision making, (2) corporate governance and firm performance, and (3) ethical principles and code of conduct. (shrink)
Synthesizing situated cognition, reinforcement learning, and hybrid connectionist modeling, a generic cognitive architecture focused on situated involvement and interaction with the world is developed in this book. The architecture notably incorporates the distinction of implicit and explicit processes.
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)
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 Fortune'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)
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)
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)
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)
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 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)
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)
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)
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)
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.
This article explores the view that computational models of cognition may constitute valid theories of cognition, often in the full sense of the term ‘‘theory”. In this discussion, this article examines various (existent or possible) positions on this issue and argues in favor of the view above. It also connects this issue with a number of other relevant issues, such as the general relationship between theory and data, the validation of models, and the practical benefits of computational modeling. All the (...) discussions point to the position that computational cognitive models can be true theories of cognition. Ó 2008 Elsevier B.V. All rights reserved. (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)
_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 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)
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)
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)
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)
Co-learning of multiple agents has been studied in co-learning settings, and how do they help, or many different disciplines under various guises. For hamper, learning and cooperation? example, the issue has been tackled by distributed • How do we characterize the process and the artiﬁcial intelligence, parallel and distributed com- dynamics of co-learning, conceptually, mathe- puting, cognitive psychology, social psychology, matically, or computationally? game theory (and other areas of mathematical econ- • how do social structures and relations interact omics), sociology, (...) anthropology, and many other with co-learning of multiple agents? related disciplines. (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)
To deal with reactive sequential decision tasks we present a learning model which is a hybrid connectionist model consisting of both localist and distributed representations based on the two level approach proposed in..
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)
We say φ is an ∀∃ sentence if and only if φ is logically equivalent to a sentence of the form ∀ x∃ y ψ(x,y), where ψ(x,y) is a quantifier-free formula containing no variables except x and y. In this paper we show that there are algorithms to decide whether or not a given ∀∃ sentence is true in (1) an algebraic number field K, (2) a purely transcendental extension of an algebraic number field K, (3) every field with characteristic (...) 0, (4) every algebraic number field, (5) every cyclic (abelian, radical) extension field over Q, and (6) every field. (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)