This paper looks at two puzzles raised by the phenomenon of inattentional blindness. First, how can we see at all if, in order to see, we must first perceptually attend to that which we see? Second, if attention is required for perception, why does it seem to us as if we are perceptually aware of the whole detailed visual field when it is quite clear that we do not attend to all that detail? We offer a general framework for thinking (...) about perception and perceptual consciousness that addresses these questions and we propose, in addition, an informal account of the relation between attention and consciousness. On this view, perceptual awareness is a species of attention. (shrink)

Alongside existing research into the social, political and economic impacts of the Web, there is a need to study the Web from a cognitive and epistemic perspective. This is particularly so as new and emerging technologies alter the nature of our interactive engagements with the Web, transforming the extent to which our thoughts and actions are shaped by the online environment. Situated and ecological approaches to cognition are relevant to understanding the cognitive significance of the Web because of the emphasis (...) they place on forces and factors that reside at the level of agent–world interactions. In particular, by adopting a situated or ecological approach to cognition, we are able to assess the significance of the Web from the perspective of research into embodied, extended, embedded, social and collective cognition. The results of this analysis help to reshape the interdisciplinary configuration of Web Science, expanding its theoretical and empirical remit to include the disciplines of both cognitive science and the philosophy of mind. (shrink)

Many debates about consciousness appear to be endless, in part because of conceptual confusions preventing clarity as to what the issues are and what does or does not count as evidence. This makes it hard to decide what should go into a machine if it is to be described as 'conscious'. Thus, triumphant demonstrations by some AI developers may be regarded by others as proving nothing of interest because the system does not satisfy *their* definitions or requirements specifications.

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think.

Context: Our body schema is not restricted to biological body boundaries (such as the skin), as can be seen in the use of a cane by a person who is visually impaired or the “rubber hands” experiment. The tool becomes a part of the body schema when the focus of our attention is shifted from the tool to the task to be performed. Problem: A body schema is formed through interactions among brain, body, tool, and environment. Nevertheless, the dynamic mechanisms (...) underlying changes in the body schema are still not fully understood. Method: To study the changing conditions of the body schema (e.g., a shift of attention), a simulation model of object discrimination was extended to differentiate between two kinds of sensitivities – sensitivity to an object being directly manipulated and sensitivity to another object being manipulated by the first. The proposed model consisted of windmills with different numbers of vanes. A model agent was required to determine the number of vanes on a windmill by touching the vanes blindly with an arm controlled by a neural network. Placing a second windmill beside the first and gearing the two windmills to move associatively resulted in the agent using the first windmill as a tool with which to discern the number of vanes on the second windmill. In other words, an agent’s body schema can shift from its arm tip to the boundary between the first and second windmills. We then introduced an experiment with a real windmill model to test the hypothesis demonstrated by the theoretical model. Results: We demonstrated that even simple computational agents can have two different sensitivities to the windmills. One agent becomes sensitive to the first windmill and insensitive to the second one. Another agent becomes insensitive to the first windmill and sensitive to the second one by using the first one as a tool. Therefore, we concluded that the boundary of the body schema was extended to the first windmill in the case of the latter agent because paying attention to the task to be performed instead of the tool itself is essential for the tool to be considered as part of the body schema. Analysis of the experiments using a computational model and human experimentation revealed that a shift from an irregular to a regular movement of a windmill is an indication of extension of the body schema. Constructivist content: Our insights are beneficial for enactive cognitive science. This is because an extended body schema questions the Cartesian separation between subject and object, and the self and the environment. (shrink)

Context: Constructivist approaches to cognition have mostly been descriptive, and now face the challenge of specifying the mechanisms that may support the acquisition of knowledge. Departing from cognitivism, however, requires the development of a new functional framework that will support causal, powerful and goal-directed behavior in the context of the interaction between the organism and the environment. Problem: The properties affecting the computational power of this interaction are, however, unclear, and may include partial information from the environment, exploration, distributed processing (...) and aggregation of information, emergence of knowledge and directedness towards relevant information. Method: We posit that one path towards such a framework may be grounded in these properties, supported by dynamical systems. To assess this hypothesis, we describe computational models inspired from swarm intelligence, which we use as a metaphor to explore the practical implications of the properties highlighted. Results: Our results demonstrate that these properties may serve as the basis for complex operations, yielding the elaboration of knowledge and goal-directed behavior. Implications: This work highlights aspects of interaction that we believe ought to be taken into account when characterizing the possible mechanisms underlying cognition. The scope of the models we describe cannot go beyond that of a metaphor, however, and future work, theoretical and experimental, is required for further insight into the functional role of interaction with the environment for the elaboration of complex behavior. Constructivist content: Inspiration for this work stems from the constructivist impetus to account for knowledge acquisition based on interaction. (shrink)

Purpose: Constructivism postulates that the perceived reality is a complex construct formed during development. Depending on the particular school, these inner constructs take on different forms and structures and affect cognition in different ways. The purpose of this article is to address the questions of how and, even more importantly, why we form such inner constructs. Approach: This article proposes that brain development is controlled by an inherent anticipatory drive, which biases learning towards the formation of forward predictive structures and (...) inverse goal-oriented control structures. This drive, in combination with increasingly complex environmental interactions during cognitive development, enforces the structuring of our conscious self, which is embedded in a constructed inner reality. Essentially, the following questions are addressed: Which basic mechanisms lead us to the construction of inner realities? How are these emergent inner realities structured? How is the self represented within the inner realities? And consequently, which cognitive structures constitute the media for conscious thought and selfconsciousness? Findings: Due to the anticipatory drive, representations in the brain shape themselves predominantly purposefully or intentionally. Taking a developmental, evolutionary perspective, we show how the brain is forced to develop progressively complex and abstract representations of the self embedded in the constructed inner realities. These self representations can evoke different stages of self-consciousness. Implications: The anticipatory drive shapes brain structures and cognition during the development of progressively more complex, competent, and flexible goal-oriented bodyenvironment interactions. Self-consciousness develops because increasingly abstract, individualizing self representations are necessary to realize these progressively more challenging environmental interactions. (shrink)

David Hume's famous riddle of induction implies a second problem related to the question of whether the laws and principles of nature might change in the course of time. Claims have been made that modern developments in physics and astrophysics corroborate the translational invariance of the laws of physics in time. However, the appearance of a new general principle of nature, which might not be derivable from the known laws of physics, or that might actually be a non-physical one (this (...) means completely independent of physical science) supports the notion that the course of nature can change in time. Here it is argued that natural selection satisfies the criteria that identify a general principle of nature which so far, appears to be non-derivable from the known laws of physics and therefore, it is likely that it arose in the course of time, thus leaving open again the quest for a true solution to Hume's second problem. (shrink)

I develop an interdisciplinary framework for understanding the nature of agents and agency that is compatible with recent developments in the metaphysics of science and that also does justice to the mechanistic and normative characteristics of agents and agency as they are understood in moral philosophy, social psychology, neuroscience, robotics, and economics. The framework I develop is internal perspectivalist. That is to say, it counts agents as real in a perspective-dependent way, but not in a way that depends on an (...) external perspective. Whether or not something counts as an agent depends on whether it is able to have a certain kind of perspective. My approach differs from many others by treating possession of a perspective as more basic than the possession of agency, representational content/vehicles, cognition, intentions, goals, concepts, or mental or psychological states; these latter capabilities require the former, not the other way around. I explain what it means for a system to be able to have a perspective at all, beginning with simple cases in biology, and show how self-contained normative perspectives about proper function and control can emerge from mechanisms with relatively simple dynamics. I then describe how increasingly complex control architectures can become organized that allow for more complex perspectives that approach agency. Next, I provide my own account of the kind of perspective that is necessary for agency itself, the goal being to provide a reference against which other accounts can be compared. Finally, I introduce a crucial distinction that is necessary for understanding human agency: that between inclinational and committal agency, and venture a hypothesis about how the normative perspective underlying committal agency might be mechanistically realized. (shrink)

Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...) serve different functions and fail for different reasons. This means that measures designed to improve model replicability may not enhance (and, in some cases, may actually damage) model reproducibility. We claim that although both are undesirable, low model reproducibility poses more of a threat to long-term scientific progress than low model replicability. In our opinion, low model reproducibility stems mostly from authors' omitting to provide crucial information in scientific papers and we stress that sharing all computer code and data is not a solution. Reports of computational studies should remain selective and include all and only relevant bits of code. (shrink)

In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no best model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical (...) aid, I note that there is no best approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on proper approaches for cognition: all approaches are a bit proper, but none will be proper enough. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition. (shrink)

Just as AI has moved away from classical AI, human-computer interaction (HCI) must move away from what I call ‘good old fashioned HCI’ to ‘new HCI’ – it must become a part of cognitive systems research where HCI is one case of the interaction of intelligent agents (we now know that interaction is essential for intelligent agents anyway). For such interaction, we cannot just ‘analyze the data’, but we must assume intentions in the other, and I suggest these are largely (...) recognized through resistance to carrying out one’s own intentions. This does not require fully cognitive agents but can start at a very basic level. New HCI integrates into cognitive systems research and designs intentional systems that provide resistance to the human agent. (shrink)