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Some Questions about Presence

Rob Clowes  
New University of Lisbon

The notion of presence has rapidly moved from a very specialized concept used to understand virtual reality and other types of human-computer interaction to something which is said to have explanatory power in psychiatry, neuroscience and the science of consciousness. This talk will look at the concept and some problems it suggests. It will then attempt to offer a new, positive account of presence.

Clash of the (Formal Probability Theory) Titans

Emmanuel Pothos  
City University London

One of the dominant traditions in cognitive modelling is classic (Bayesian) probability (CP) theory. Yet considerable evidence has accumulated that human judgment often goes against classical principles.

We discuss quantum probability (QP) theory as an alternative formal probabilistic framework for understanding cognition. In QP theory, probabilistic assessment is often strongly context and order dependent, individual states can be superposition states (which are indefinite with respect to some specific judgment), and composite systems can be entangled (they cannot be decomposed into simpler subsystems). We review two fundamental empirical findings (the conjunction fallacy, violations of the sure thing principle in prisoner's dilemma games), which have persistently challenged classical theory, yet have natural accounts within quantum theory.

20 Years After "The Embodied Mind" - Why is cognitivism alive and kicking?

Vincent Müller 
Anatolia College, Thessaloniki

Taking the classic book by Varela, Thomson & Rosch as a starting point, I want to suggest that the influence of embodied positions has been a changing of positions: Cognitivism has found ways to retreat and regroup at positions that have better fortification. I want to take a look at two such positions that share one view: a) Humans and other natural cognitive agents are computational information processors made up of several modules that take in symbolic representations of the world, process these according to specified rules and then produce a symbolic output. What might be called agent-based ‘cognitivism’ is now often limited to certain aspects of cognition, especially those related to conscious processes; while it might concede that there are other aspects to cognition that are not computational. b) A second development, influenced by technical AI, is to assume that cognitive features can be generated by fundamental computational processes that are purely syntactic, not implying any particular theory of the mind, in fact being compatible with embodiment, or supplemented by embodiment (e.g. for 'grounding').

Given the regrouping of the opposition, there is a danger that 'embodiment' continues to loose out if it continues to direct its attacks against positions that are now empty and unimportant. Perhaps embodiment has now run its course, having contributed to a refinement of computational models of the mind?

Simulation, Internal Representations and Internal Models

Germund Hesslow  
University of Lund

The talk will summarise the current evidence for a view of cognitive function as internal simulation of action and perception, that is, covert behaviour and perceptual activity elicited by internal brain activity. It will be argued that cogntive functions that have often been taken to require internal representations or internal models of reality, such as explicit knowledge, declarative memory and mental maps, can be acclounted for more parsimoniously by internal simulation.

The Long and Short of Working Memory

Natasha Sigala  
Brighton and СÀ¶ÊÓƵ Medical School, СÀ¶ÊÓƵ

Natasha Sigala will discuss electrophysiological and imagining evidence of the neural correlates of working memory.

Turing's Embryonic Biology

Margaret Boden  
СÀ¶ÊÓƵ

Turing was the first to use a digital computer to model self-organization. In his last published paper (1952), he showed how familiar laws of physics imply that interactions between diffusing chemicals, in an undifferentiated egg/embryo, could result in waves and/or regions of differing chemical concentrations. These might then give rise to anatomical features such as rings of petals or tentacles, stripes or dappling on surfaces, 3D structures (e.g. gastrulation), and neuronal circuits.  In short, physics is the basis of morphogenesis (the development of form, or shape).

His computers were far too simple to allow more than minimal execution of his theoretical ideas. Now, that's no longer so.  Developmental biologists have taken up Turing's ideas.  Some of them emphasise (which Turing did not) that these principles of morphogenesis are prior to Darwinian natural selection. And a few (e.g. Brian Goodwin) aim to discover systematic "laws of form " generating all possible biological shapes. 

(Some background is in my book Mind as Machine: A History of Cognitive Science. See sections 2.vi.e-f, 15.iii, 15.iv, and 15.ix.c.)

Context and Serendipity in Computational Creativity

Alison Pease  
University of Edinburgh

Abstract: Computational Creativity is the study and simulation, by computational means, of behaviour, natural and artificial, which would, if observed in humans, be deemed creative. In this talk I look to examples of human creativity to suggest aspects of creativity which have not yet received much attention from the CC community. In particular, I consider serendipitous discovery, and whether it is possible to build a system which makes serendipitous discoveries. I also consider the role of framing information in creativity; that is, the context around a piece of creative work, including the artist themselves, their motivations for creating the piece and how they think it fits into a current artistic landscape. Finally, I consider which methods are appropriate, or inappropriate, for measuring progress in CC.

Biography: Alison Pease is a Research Associate on the Computational Creativity Theory project at Imperial College London. Her main interest is in creativity in mathematics, and has investigated the use of analogies, conceptual-blends and embodied reasoning in mathematics. She holds a PhD in Artificial Intelligence, in which she built a model of social interaction between mathematicians, based on a theory by the philosopher Imre Lakatos. She has a background in philosophy and mathematics and was a mathematics teacher for several years.