Alexander Riegler

Understanding representation in the cognitive sciences

This paper discusses the notion of representation and outlines the ideas and questions which led to the organization of this volume. We argue for a distinction between the classical view of referential representation, and the alternative concept of system-relative representation. The latter refers to situated cognitive processes whose dynamics are merely modulated by their environment rather than being instructed and determined by it.

When is a cognitive system embodied

For cognitive systems, embodiment appears to be of crucial importance. Unfortunately, nobody seems to be able to define embodiment in a way that would prevent it from also covering its trivial interpretations such as mere situatedness in complex environments. The paper focuses on the definition of embodiment, especially whether physical embodiment is necessary and/or sufficient for cognitive systems. Cognition is characterized as a continuous complex process rather than ahistorical logical capability. Furthermore, the paper investigates the relationship between cognitive embodiment and the issues of understanding, representation and task specification.

The role of anticipation in cognition

According to the standard definition of anticipatory systems, anticipation is based on a predictive model of the system itself and its environment. The paper abandons this perspective of weak anticipation in favor of what has been called strong anticipation. It is proposed that anticipation is a consequence of canalization caused by the organization of the structural building-blocks of which the system in question consists. Strong anticipation can account for the anticipatory behavior in animals to which we would not impute the ability of creating internal models of themselves.

Extending the Hegselmann–Krause Model III: From Single Beliefs to Complex Belief States

In recent years, various computational models have been developed for studying the dynamics of belief formation in a population of epistemically interacting agents that try to determine the numerical value of a given parameter. Whereas in those models, agents’ belief states consist of single numerical beliefs, the present paper describes a model that equips agents with richer belief states containing many beliefs that, moreover, are logically interconnected. Correspondingly, the truth the agents are after is a theory (a set of sentences of a given language) rather than a numerical value. The agents epistemically interact with each other and also receive evidence in varying degrees of informativeness about the truth. We use computer simulations to study how fast and accurately such populations as wholes are able to approach the truth under differing combinations of settings of the key parameters of the model, such as the degree of informativeness of the evidence and the weight the agents give to the evidence.

Does Representation Need Reality

This paper discusses the notion of representation and outlines the ideas and questions which led to the organization of this volume. We argue for a distinction between the classical view of referential representation, and the alternative concept of system-relative representation. The latter refers to situated cognitive processes whose dynamics are merely modulated by their environment rather than being instructed and determined by it.

Extending the Hegselmann-Krause model I

Hegselmann and Krause have developed a simple yet powerful computational model for studying the opinion dynamics in societies of epistemically interacting truth-seeking agents. We present various extensions of this model and show their relevance to the investigation of socio-epistemic questions, with an emphasis on normative questions. Agent-based computer simulations have been successfully employed in the study of broadly social processes for over thirty years now. Researchers have investigated by these means such diverse phenomena as the spread of wealth in a population, the emergence and evolution of friendship networks, integration and segregation of different racial groups, the transmission of cultural values, and the propagation of infectious diseases. It is only in the past decade that agent-based simulations have come to be used for studying distinctively socio-epistemic (or socio-doxastic) questions, such as, most notably, questions concerning the roles various types of social interaction play in the acquisition and transmission of beliefs and knowledge. Pioneering work in this area has been carried out by Rainer Hegselmann and Ulrich Krause, who have developed, and systematically investigated, a simple yet already quite powerful model for simulating the opinion dynamics in societies of epistemically interacting truthseeking agents. By thus initiating what they have termed “Computer Aided Social Epistemology,” they have, in our eyes, made an important contribution to social epistemology. After all, social epistemology can be considered to be as much a branch of philosophy as of social science, and one may thus expect that it is able to profit from the deployment of simulation tools no less than the more traditional social sciences have been (and still are). Nevertheless, it has been generally recognized that, in addition to considerable virtues, the Hegselmann–Krause (HK) model also has some important inherent limitations, these being largely due to the fact that the model is starkly idealized in several respects. The present paper proposes various extensions of the model that do away 1See Epstein and Axtell [1996] and the references given there. 2See, e.g., Hegselmann and Krause [2002], [2005], and [2006]; see also Dittmer [2001], Fortunato [2004], and Lorenz [2007]. Similar work is to be found in Deffuant et al. [2000], Weisbuch et al. [2002], and Ramirez-Cano and Pitt [2006].

THE COGNITIVE RATCHET - THE RATCHET EFFECT AS A FUNDAMENTAL PRINCIPLE IN EVOLUTION AND COGNITION

Is the evolution and performance of cognition an asymmetric, directed process? The standard externalist definition of evolution as a mechanism of variation and selection cannot account for directed developments such as an increase in complexity of cognition. A separate cause that is responsible for complexification requires us to deviate from the usual description of cognition as ahistorical logical problem-solving: the anticipation-driven nature of behavior, and, hence cognition based on a ratchet effect. On a structural level it is evident that the growth of behavioral competence, similar to biological structures, must build on previously available components, thus yielding a canalization of development. This unavoidably introduces asymmetry in the cognitive evolution. Numerous examples show the relevance of the proposed mechanisms in biology, psychology, and the artificial sciences.

Natural or internal selection? the case of canalization in complex evolutionary systems

Using biological examples and theoretical arguments, the case is presented for extending the notion of natural selection to include internal selection in order to account for the evolution of complex systems. It is suggested that we take into consideration internal factors that arise from the hierarchical dynamics of complex systems. In addition to environmental selection, it is argued, decisive constraints are created by the system itself. Canalization is shown to be an indispensable ingredient for evolutionary processes in both biological and artificial complex systems. In artificial life systems canalization is not only an instrument for controlling complexity, it also increases the speed and stability of evolutionary processes.

Like cats and dogs: Radical constructivism and evolutionary epistemology

I identify two similarities between evolutionary epistemology (EE) and radical constructivism (RC): (1) They were founded primarily by biologists and (2) their respective claims can be related to Kant. Despite this fact there seems to be an abyss between them. I present an attempt to reconcile this gap and characterize EE as the approach that focuses on external behaviour, while RC emphasizes the perspective from within. The central concept of hypothetical realism is criticized as unnecessarily narrowing down the scope of EE. Finally, methodological and philosophical conclusions are drawn.

Inclusive worldviews: Interdisciplinary research from a radical constructivist perspective

Interdisciplinary inquiry presupposes an open worldview to enable the researcher to transcend the confinements of a specific discipline in order to become aware of aspects that are necessary to satisfyingly solve a problem. Radical constructivism offers a way of engineering such interdisciplinarity that goes beyond mere multi or pluridisciplinary approaches. In this paper I describe epistemological and methodological aspects of interdisciplinarity, discuss typical problems it faces, and carve out its relationship with knowledge and communication from a constructivist perspective. Five implications for interdisciplinary practice and science education conclude the paper.