From this post-reflective point of view, the book argues for an intimate relationship between cognition, sensorimotor embodiment, and the integrative character ...

This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with the environment, is mediated by (...) affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot. (shrink)

This article presents a formal theory of robot perception as a form of abduction. The theory pins down the process whereby low‐level sensor data is transformed into a symbolic representation of the external world, drawing together aspects such as incompleteness, top‐down information flow, active perception, attention, and sensor fusion in a unifying framework. In addition, a number of themes are identified that are common to both the engineer concerned with developing a rigorous theory of perception, such as the one on (...) offer here, and the philosopher of mind who is exercised by questions relating to mental representation and intentionality. (shrink)

Our aim in this reply is to defend Global Workspace theory (GWT) from the challenge of Block's article. We argue that Block's article relies on an outdated and imprecise concept of access, and perpetuates a common misunderstanding of GWT that conflates the global workspace with working memory. In the light of the relevant clarifications, Block's conclusion turns out to be unwarranted, and the basic tenets of GWT emerge unscathed.

This paper presents a computer model of cortical broadcast and competition based on spiking neurons and inspired by the hypothesis of a global neuronal workspace underlying conscious information processing in the human brain. In the model, the hypothesised workspace is realised by a collection of recurrently inter-connected regions capable of sustaining and disseminating a reverberating spatial pattern of activation. At the same time, the workspace remains susceptible to new patterns arriving from outlying cortical populations. Competition among these cortical populations for (...) influence on the workspace is effected by a combination of mutual inhibition and top-down amplification. (shrink)

The objectives of this article are twofold. First, by denying the dualism inherent in attempts to load metaphysical significance on the inner/outer distinction, it defends the view that scientific investigation can approach consciousness in itself, and is not somehow restricted in scope to the outward manifestations of a private and hidden realm. Second, it provisionally endorses the central tenets of global workspace theory, and recommends them as a possible basis for the sort of scientific understanding of consciousness thus legitimised. However, (...) the article goes on to argue that global workspace theory alone does not constitute a fully worked-out objective account of the conscious subject. This requires additional attention to be paid to the issue of embodiment, and to the possibility of indexicality that arises when an instantiation of the global workspace architecture inhabits a spatially localised body. (shrink)

Artificial Intelligence is making rapid and remarkable progress in the development of more sophisticated and powerful systems. However, the acknowledgement of several problems with modern machine learning approaches has prompted a shift in AI benchmarking away from task-oriented testing towards ability-oriented testing, in which AI systems are tested on their capacity to solve certain kinds of novel problems. The Animal-AI Environment is one such benchmark which aims to apply the ability-oriented testing used in comparative psychology to AI systems. Here, we (...) present the first direct human-AI comparison in the Animal-AI Environment, using children aged 6–10. We found that children of all ages were significantly better than a sample of 30 AIs across most of the tests we examined, as well as performing significantly better than the two top-scoring AIs, “ironbar” and “Trrrrr,” from the Animal-AI Olympics Competition 2019. While children and AIs performed similarly on basic navigational tasks, AIs performed significantly worse in more complex cognitive tests, including detour tasks, spatial elimination tasks, and object permanence tasks, indicating that AIs lack several cognitive abilities that children aged 6–10 possess. Both children and AIs performed poorly on tool-use tasks, suggesting that these tests are challenging for both biological and non-biological machines. (shrink)

According to the singularity hypothesis, rapid and accelerating technological progress will in due course lead to the creation of a human-level artificial intelligence capable of designing a successor artificial intelligence of significantly greater cognitive prowess, and this will inaugurate a series of increasingly super-intelligent machines. But how much sense can we make of the idea of a being whose cognitive architecture is qualitatively superior to our own? This article argues that one fundamental limitation of human cognitive architecture is an inbuilt (...) commitment to a metaphysical division between subject and object, a commitment that could be overcome in an artificial intelligence lacking our biological heritage. (shrink)

Murray Shanahan, Int. J. Mach. Conscious., 06, 63 (2014). DOI: 10.1142/S1793843014400101.