The role of complex systems theory in cognitive science (original) (raw)
Related papers
Contextual emergence of mental states from neurodynamics
The emergence of mental states from neural states by partitioning the neural phase space is analyzed in terms of symbolic dynamics. Well-defined mental states provide contexts inducing a criterion of structural stability for the neurodynamics that can be implemented by particular partitions. This leads to distinguished subshifts of finite type that are either cyclic or irreducible. Cyclic shifts correspond to asymptotically stable fixed points or limit tori whereas irreducible shifts are obtained from generating partitions of mixing hyperbolic systems. These stability criteria are applied to the discussion of neural correlates of consiousness, to the definition of macroscopic neural states, and to aspects of the symbol grounding problem. In particular, it is shown that compatible mental descriptions, topologically equivalent to the neurodynamical description, emerge if the partition of the neural phase space is generating. If this is not the case, mental descriptions are incompatible or complementary. Consequences of this result for an integration or unification of cognitive science or psychology, respectively, will be indicated.
Dynamical Systems Theory in Cognition: Are We Really Gaining?
2011
Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that this DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN), are the ones that are causing trouble in the philosophy of science speculation, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonability of a possibility.
Complex Systems, Brain, and Consciousness (Reading Group Syllabus)
An a priori definition of complexity cannot be given, nor is it viable to propose one for the reason that every complex system differs in character and organization. Thus, the only possible course of action in understanding complex systems is by observing the characteristics those systems exhibit. However, some features have been deemed necessary (although not sufficient) for regarding a system complex as opposite to complicated or merely simple systems. A working definition of this sort describes a complex system as a composite organization of many interdependent parts that are displaying rich array of nonlinear interactions and/or adaptive relations that result in complex ('emergent') collective behavior. In this sense, it is important to distinguish complex from complicated systems since complicated systems can and often do have many components and perform highly sophisticated operations. For example, the Large Hadron Collider is a complicated system; we can deconstruct it to its constituent parts and account for their function within a system. By doing so we are able to predict the systems behavior. On the other hand, a flock of birds is a complex system. Given the part's properties, i.e. single bird, one cannot fully account for the properties of the whole, i.e. the flock, making those systems more than just the sum of their parts. Complexity talk has become fashionable over the recent decade or so. Its applications are numerous. One of them is in the Cognitive Neuroscience research project. This is mostly done through the framework of complex dynamical systems which presents a radical shift of methodology. However, there are two problems emerging from this and, thus, two main aims of this reading group. Firstly, the very concept of 'complexity' is complex. Can we talk about complexity as an umbrella term or are there only specific cases of complexity? Similarly, should this, and in what way, change the application of the theory itself to the particular systems? In addition, complex systems theory uses opaque concepts such as emergence that are heavily burden philosophically. Hence, the first order of business is to understand complex systems and, subsequently, examine them from a philosophical perspective. On the other hand, theories like Integrated Information Theory (IIT) have recently emerged in this framework. These theories aim to account for phenomenology and capture the notion of consciousness. However, the main issue remains the same throughout the theories: the very application to " higher order " cognitive processes is questionable, since complex dynamical systems don't necessarily account for 'how things work' or 'why things happen'. Hence, our second aim is to examine some of these theories more closely.
A complex-systems perspective on the" computation vs. dynamics" debate in cognitive science
1998
Abstract I review the purported opposition between computational and dynamical approaches in cognitive science. I argue that both computational and dynamical notions will be necessary for a full explanatory account of cognition, and give a perspective on how recent research in complex systems can lead to a much needed rapprochement between computational and dynamical styles of explanation.
1995
Recently, a new approach to modeling cognitive phenomena has been gaining recognition: the dynamical systems approach. Proponents of this theory claim to have identified a new paradigm for the study of cognition which is superior to both symbolicism and connectionism.
Dynamical Systems in Cognition: Are We Really Gaining?
Dynamical Systems Theory (DST) claims to be an epistemological weapon particularly broad and rich in providing a fair explanatory account of the operations of our mind. However, the very features that DST espouses as reasons for having an edge over Computational Theory of Mind (CTM) and Artificial Neural Networks (ANN) are the ones that are causing trouble in the philosophy of science, especially regarding issues of Explanation. This paper aims to suggest some possible problems that could arise from the application of DST’s characteristically abstract mathematical framework to the study of the mind. As I have not found anything that suggests something like this, my aim is to at least show the reasonableness of a possibility.
The Emergence of Mind in a Physical World
2018
The main purpose of this monograph is to respond to the reiterated criticisms that some reductionist philosophers, especially Jaegwon Kim and David Papineau, have developed of the non-reductive physicalist explanation of the causal power or relevance of the higher level or special sciences’ properties; properties of sciences as chemistry, biology and, especially, psychology. I argue that most of contemporary analytic philosophy is mistaken in assuming a physicalist proposal on the basis of the metaphysical supervenience theory of the higher level properties on their microphysical bases, the theory that we call microphysicalism, because this proposal has not only deep empirical but conceptual problems. Because the most accepted version of non-reductive physicalism – the current functionalist proposal – is committed to microphysicalism, Kim and the reductionists are right in their conceptual criticisms of the inability to account for the reality and irreducibility of the causal powers of the higher level properties within this physicalist framework. But they are wrong in claiming that the failure of the current functionalist proposal implies a general failure of any non-reductive physicalism. Emergentism is articulated as a type macrophysicalist theory because it considers that the special properties are metaphysically dependent on but not metaphysically determined by and, therefore, not reducible to their microphysical bases. This proposal claims that higher level causation is articulated combining the under-determination of the lower level causal processes, along with the instantiation of higher level causal properties and laws that constrain and select from the different and under-determined causal alternatives that the properties and laws that govern the lower processes leave open. As a final and general conclusion we can say that macrophysicalism or emergentism is not only a coherent and well suited conceptual proposal about the causal functioning of the different levels of composition and organization of our physical world, but that as far as we know it can be its most plausible empirical articulation.
Complex Systems Approach to the Hard Problem of Consciousness
Consciousness has been the bone of contention for philosophers throughout centuries. Indian philosophy largely adopted lived experience as the starting point for its explorations of consciousness. For this reason, from the very beginning, experience was an integral way of grasping consciousness, whose validity as a tool was considered self-evident. Thus, in Indian philosophy, the question was not to move from the brain to mind but to understand experience of an individual and how such an experience is determined through mental structures (and secondarily, the preoccupation with the brain and its relation to the mind). In contrast, cognitive science (the study of mind and cognition through 1 interdisciplinary methods, with emphasis on computational methods) found its debates soaked in discussion which primarily involved the brain and mind. Experience was not considered a primary source of information and its validity had to be established to consider it a source of information of min...