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..
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. (PsycINFO Database Record (c) 2012 APA, all rights reserved). (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.
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)
Does a board with greater gender diversity make better investment decisions? Drawing on Austrian economic cycle theory and work groups theory, we argue that such board openness will help male board members to overcome gender biases, discrimination, and conflicts; integrate different perspectives under the economic cycle and crisis; and foster an environment in which better decisions are made. The results of an empirical study of 14,609 firm-quarter observations from 1,555 listed firms in China between 2007 and 2009 strongly support our (...) arguments. We find that a Chinese board is more likely to accept female directorship during an economic crisis than during an economic prosperity stage. Boards with greater gender diversity are more likely to make tough, counter-cyclical investments to improve firm performance during a crisis. Our study enriches the board decision-making literature by exploring the impacts of board gender diversity on firm performance within the context of an economic crisis. The results of our study also carry significant managerial implications for overcoming gender stereotypes, biases, and prejudices on a board. (shrink)
This paper discusses essential motivational representations necessary for a comprehensive computational cognitive architecture. It hypothesizes the need for implicit drive representations, as well as explicit goal representations. Drive representations consist of primary drives — both low-level primary drives (concerned mostly with basic physiological needs) and high-level primary drives (concerned more with social needs), as well as derived (secondary) drives. On the basis of drives, explicit goals may be generated on the ﬂy during an agent’s interaction with various situations. These motivational (...) representations help to make cognitive architectural models more comprehensive and provide deeper explanations of psychological processes. This work represents a step forward in making computational cognitive architectures better reﬂections of the human mind and all its motivational complexity and intricacy. (shrink)
This study examines whether the gender of the directors on fully independent audit committees affects the ability of the committees in constraining earnings management and thus their effectiveness in overseeing the financial reporting process. Using a sample of 525 firm-year observations over the period 2003 to 2005, we are unable to identify an association between the proportion of female directors on audit committees and the extent of earnings management.
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)
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 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)
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)
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 paper addresses weighting and partitioning in complex reinforcement learning tasks, with the aim of facilitating learning. The paper presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with di erential weighting in these regions, to exploit di erential characteristics of regions and di erential characteristics of agents to reduce the learning complexity of agents (and their function approximators) and thus to facilitate the learning overall. It analyzes, in reinforcement learning (...) tasks, di erent ways of partitioning a task and using agents selectively based on partitioning. Based on the analysis, some heuristic methods are described and experimentally tested. We nd that some o -line heuristic methods performed the best, signi cantly better than single-agent models. (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)
‘Mindfulness’ has become a buzzword, yet its meaning and origins have received relatively little critical consideration. This article places the current ‘mindfulness movement’ in context, examining the evolving discourse surrounding the concept of mindfulness. Through the first systematic etymology of the term, drawing from old Western and Buddhist writings, contemporary psychology and popular media, it is established that the contemporary understanding of mindfulness has been substantially simplified and divorced from its origins. However, quantitative data suggests that this manoeuvre was essential (...) for the mainstreaming of the concept. Moreover, the resulting momentum has stimulated a new and dynamic discourse about the relationship between ‘secular’ mindfulness and Buddhism, sparking questions about ‘McMindfulness’, ‘stealth’ Buddhism and cultural imperialism. Therefore, this article argues that the recontextualisation of mindfulness created the scaffolding that supported the emergence of a deeper and more meaningful conversation about its implications for Buddhism and society that we see today. (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)
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)
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)
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)
_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 review addresses the current and future potential of nanomedicine, and its ethical considerations within the comprehensive framework of the four dimensions of medical ethics: Beneficence, Non-Maleficence, Respect, and Justice. From this perspective, the ethical considerations for nanomedicine are not novel, but have been addressed by precedents throughout the history of medicine. While these ethical challenges are not unique to nanomedicine, some require additional consideration, given the envisioned pervasive impact of nanomedicine on society.
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.
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 paper examines the effect of corporate social responsibility on the number of bond covenants. We find that a high CSR score has a negative association with the number of bond covenants. Moreover, our results are more pronounced for firms with a high bid-ask spread and high agency costs. Our analysis highlights the effect of the good stakeholder relationship on the bond contracts.
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)
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)
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)
Using private benefits of control and earnings management data from 41 countries and regions, we provide strong evidence that cultures, together with legal rules and law enforcement, play a critical role in shaping corporate behavior. More specifically, we find that private benefits of control are larger and earnings management is more severe in collectivist as opposed to individualist cultures, consistent with the argument that agency problems between corporate insiders and outside investors are severe in collectivist culture. These results are robust (...) to the inclusion of controls for country wealth, economic heterogeneity across countries, and international differences in ownership concentration. (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)
This study examines whether sanctions imposed by the China Securities Regulatory Commission against individual auditors result in greater auditor conservatism. Using a difference-in-differences research design, we find that clients of sanctioned individual auditors have lower discretionary accruals in the post-sanction period than in the pre-sanction period when compared to a matched control group of clients audited by individual auditors who were not sanctioned. Our findings suggest that sanctions imposed by the CSRC on individual auditors can lead to improvements in audit (...) quality by increasing the conservatism of the sanctioned auditors. That is, individual auditors are more likely to resist their clients’ income-increasing accounting manipulations after being sanctioned by the CSRC. (shrink)
Learners are able to use 2 different types of knowledge to perform a skill. One type is a conscious mental model, and the other is based on memories of instances. The authors conducted 3 experiments that manipulated training conditions designed to affect the availability of 1 or both types of knowledge about an artificial grammar. Participants were tested for both speed and accuracy of their ability to generate letter sequences. Results indicate that model-based training leads to slow accurate responding. Memorybased (...) training leads to fast, less accurate responding and highest achievement when perfect accuracy was not required. Evidence supports participants’ preference for using the memory-based mode when exposed to both types of training. Finally, the accuracy contributed by model-based training declined over a retention interval. (shrink)
Computational cognitive models hypothesize internal mental processes of human cognitive activities and express such activities by computer programs Such computational models often consist of many components and aspects Claims are often made that certain aspects of the models play a key role in modeling but such claims are sometimes not well justi ed or explored In this paper we rst review some fundamental distinctions and issues in computational modeling We then discuss in principle systematic ways of identifying the source of (...) power in the models.. (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..