Aaron Sloman

"The Emperor's New Mind" by Roger Penrose has received a great deal of both praise and criticism. This review discusses philosophical aspects of the book that form an attack on the "strong" AI thesis. Eight different versions of this thesis are distinguished, and sources of ambiguity diagnosed, including different requirements for relationships between program and behaviour. Excessively strong versions attacked by Penrose (and Searle) are not worth defending or attacking, whereas weaker versions remain problematic. Penrose (like Searle) regards the notion of an algorithm as central to AI, whereas it is argued here that for the purpose of explaining mental capabilities the architecture of an intelligent system is more important than the concept of an algorithm, using the premise that what makes something intelligent is not what it does but how it does it. What needs to be explained is also unclear: Penrose thinks we all know what consciousness is and claims that the ability to judge Go "del's formula to be true depends on it. He also suggests that quantum phenomena underly consciousness. This is rebutted by arguing that our existing concept of "consciousness" is too vague and muddled to be of use in science. This and related concepts will gradually be replaced by a more powerful theory-based taxonomy of types of mental states and processes. The central argument offered by Penrose against the strong AI thesis depends on a tempting but unjustified interpretation of Goedel's incompleteness theorem. Some critics are shown to have missed the point of his argument. A stronger criticism is mounted, and the relevance of mathematical Platonism analysed. Architectural requirements for intelligence are discussed and differences between serial and parallel implementations analysed.

This is a 5 page summary with three diagrams of the main objectives and some work in progress at the University of Birmingham Cognition and Affect project. involving: Professor Glyn Humphreys (School of Psychology), and Luc Beaudoin, Chris Paterson, Tim Read, Edmund Shing, Ian Wright, Ahmed El-Shafei, and (from October 1994) Chris Complin (research students). The project is concerned with "global" design requirements for coping simultaneously with coexisting but possibly unrelated goals, desires, preferences, intentions, and other kinds of motivators, all at different stages of processing. Our work builds on and extends seminal ideas of H.A.Simon (1967). We are exploring "broad and shallow" architectures combining varied capabilities most of which are not implemented in great depth. The poster summarises some ideas about management and meta-management processes, attention filtering, and the relevance to emotional states involved "perturbances", where there is partial loss of control of attention.

Animals and robots perceiving and acting in a world require an ontology that accommodates entities, processes, states of affairs, etc., in their environment. If the perceived environment includes information - processing systems, the ontology should reflect that. Scientists studying such systems need an ontology that includes the first - order ontology characterising physical phenomena, the second - order ontology characterising perceivers of physical phenomena, and a third order ontology characterising perceivers of perceivers, including introspectors. We argue that second - and third - order ontologies refer to contents of virtual machines and examine requirements for scientific investigation of combined virtual and physical machines, such as animals and robots. We show how the CogAff architecture schema, combining reactive, deliberative, and meta - management categories, provides a first draft schematic third - order ontology for describing a wide range of natural and artificial agents. Many previously proposed architectures use only a subset of CogAff, including subsumption architectures, contention - scheduling systems, architectures with Ôexecutive functionsÕ and a variety of types of ÔOmegaÕ architectures. Adding a multiply - connected, fastacting ÔalarmÕ mechanism within the CogAff framework accounts for several varieties of emotions. H - CogAff, a special case of CogAff, is postulated as a minimal architecture specification for a human - like system. We illustrate use of the CogAff schema in comparing H - CogAff with Clarion, a well known architecture. One implication is that reliance on concepts tied to observation and experiment can harmfully restrict explanatory theorising, since what an information processor is doing cannot, in general, be determined by using the standard observational techniques of the physical sciences or laboratory experiments. Like theoretical physics, cognitive science needs to be highly speculative to make progress. Ó 2004 Published by Elsevier B. V.

Emotions involve complex processes produced by interactions between motives, beliefs, percepts, etc. E.g. real or imagined fulfilment or violation of a motive, or triggering of a 'motive-generator', can disturb processes produced by other motives. To understand emotions, therefore, we need to understand motives and the types of processes they can produce. This leads to a study of the global architecture of a mind. Some constraints on the evolution of minds are disussed. Types of motives and the processes they generate are sketched.

How can a virtual machine X be implemented in a physical machine Y? We know the answer as far as compilers, editors, theorem-provers, operating systems are concerned, at least insofar as we know how to produce these implemented virtual machines, and no mysteries are involved. This paper is about extrapolating from that knowledge to the implementation of minds in brains. By linking the philosopher's concept of supervenience to the engineer's concept of implementation, we can illuminate both. In particular, by showing how virtual machines can be implemented in causally complete physical machines, and still have causal powers, we remove some philosophical problems about how mental processes can be real and can have real effects in the world even if the underlying physical implementation has no causal gaps. This requires a theory of ontological levels.

Since the 1970s AI as a science has progressively fragmented into many activities that are very narrowly focused. It is not clear that work done within these fragments can be combined in the design of a human-like integrated system – long held as one of the goals of AI as science. A strategy is proposed for reintegrating AI based around a backward-chaining analysis to produce a roadmap with partially ordered milestones, based on detailed scenarios, that everyone can agree are worth achieving, even when they disagree about means.

In lieu of an abstract, here is a brief excerpt of the content:Response to the CommentariesIan Wright, Aaron Sloman, and Luc BeaudoinWe are very grateful for the care with which the commentators have read our paper, and the sympathy with which they treated what we acknowledged to be at best a preliminary attempt to make sense of a range of phenomena involving grief and other emotions in terms of our draft architecture. We are fortunate to have commentators that are so much in sympathy with what we have written.The comments of Castelfranchi and Miceli draw attention to a problem that we expect many readers to bring up, namely that there is a notion of “information processing” that cannot carry the explanatory weight that we attach to our information processing architecture. We believe that there is a concept of “information processing” such as is used by engineers who design software systems to perform such tasks as controlling an aircraft. We claim that within an appropriate system architecture, information processing states can have all the causal powers that we require for states like pain, pleasure, and the like. However this is not obvious, and defending this claim will have to await another occasion.Lloyd helpfully illustrates the relevance of our proposed architecture even to the effects of imagining the death of a loved one. He also makes the useful observation that second-order states can arise when a person who is suffering because events violate some important motivator, discovers that nothing can be done about the cause of the suffering, and then suffers even more because of feeling helpless in that situation. We acknowledge that these are phenomena that the architecture will have to accommodate, and accept the challenge to demonstrate this in due course.We believe that there is enough commonality between the commentators and ourselves to support our view that the research community is on the verge of an important new breakthrough in the study of mind, in which philosophers, psychologists, therapists, brain scientists, and AI researchers can collaborate fruitfully, and from which profound practical and theoretical consequences will follow.Related ArticlesFeature Article: Towards a Design-Based Analysis of Emotional EpisodesCommentary: Commentary by LloydCommentary: Commentary by Miceli and CastelfranchiCommentary: Commentary by BodenResponse: Response to the CommentariesCopyright © 1996 The Johns Hopkins University Press...

Most philosophers appear to have ignored the distinction between the broad concept of Virtual Machine Functionalism (VMF) described in Sloman&Chrisley (2003) and the better known version of functionalism referred to there as Atomic State Functionalism (ASF), which is often given as an explanation of what Functionalism is, e.g. in Block (1995). One of the main differences is that ASF encourages talk of supervenience of states and properties, whereas VMF requires supervenience of machines that are arbitrarily complex networks of causally interacting (virtual, but real) processes, possibly operating on different time-scales, examples of which include many different procesess usually running concurrently on a modern computer performing various tasks concerned with handling interfaces to physical devices, managing the file system, dealing with security, providing tools, entertainments, and games, and possibly processing research data. Another example of VMF would be the kind of functionalism involved in a large collection of possibly changing socio-economic structures and processes interacting in a complex community, and yet another is illustrated by the kind of virtual machinery involved in the many levels of visual processing of information about spatial structures, processes, and relationships (including percepts of moving shadows, reflections, highlights, optical-flow patterns and changing affordances) as you walk through a crowded car-park on a sunny day: generating a whole zoo of interacting qualia. (Forget solitary red patches, or experiences thereof.) Perhaps VMF should be re-labelled "Virtual MachinERY Functionalism" because the word 'machinery' more readily suggests something complex with interacting parts. VMF is concerned with virtual machines that are made up of interacting concurrently active (but not necessarily synchronised) chunks of virtual machinery which not only interact with one another and with their physical substrates (which may be partly shared, and also frequently modified by garbage collection, metabolism, or whatever) but can also concurrently interact with and refer to various things in the immediate and remote environment (via sensory/motor channels, and possible future technologies also). I.e. virtual machinery can include mechanisms that create and manipulate semantic content, not only syntactic structures or bit patterns as digital virtual machines do. Please note: Click on the title above or the link below to read the paper. I prefer to keep all my papers freely accessible on my web site so that I can correct mistakes and add improvements. http://www.cs.bham.ac.uk/research/projects/cogaff/misc/vm-functionalism.html This is now part of the Meta-Morphogenesis project: http://www.cs.bham.ac.uk/research/projects/cogaff/misc/meta-morphogenesis.html

This paper discusses some of the requirements for the control architecture of an intelligent human-like agent with multiple independent dynamically changing motives in a dynamically changing only partly predictable world. The architecture proposed includes a combination of reactive, deliberative and meta-management mechanisms along with one or more global ``alarm'' systems. The engineering design requirements are discussed in relation our evolutionary history, evidence of brain function and recent theories of Damasio and others about the relationships between intelligence and emotions. (The paper was completed in haste for a deadline and I forgot to explain why Descartes was in the title. See Damasio 1994.).

Extract from Hofstadter's revew in Bulletin of American Mathematical Society : http://www.ams.org/journals/bull/1980-02-02/S0273-0979-1980-14752-7/S0273-0979-1980-14752-7.pdf "Aaron Sloman is a man who is convinced that most philosophers and many other students of mind are in dire need of being convinced that there has been a revolution in that field happening right under their noses, and that they had better quickly inform themselves. The revolution is called "Artificial Intelligence" (Al)-and Sloman attempts to impart to others the "enlighten- ment" which he clearly regrets not having experienced earlier himself. Being somewhat of a convert, Sloman is a zealous campaigner for his point of view. Now a Reader in Cognitive Science at Sussex, he began his academic career in more orthodox philosophy and, by exposure to linguistics and AI, came to feel that all approaches to mind which ignore AI are missing the boat. I agree with him, and I am glad that he has written this provocative book. The tone of Sloman's book can be gotten across by this quotation (p. 5): "I am prepared to go so far as to say that within a few years, if there remain any philosophers who are not familiar with some of the main developments in artificial intelligence, it will be fair to accuse them of professional incom- petence, and that to teach courses in philosophy of mind, epistemology, aesthetics, philosophy of science, philosophy of language, ethics, metaphysics, and other main areas of philosophy, without discussing the relevant aspects of artificial intelligence will be as irresponsible as giving a degree course in physics which includes no quantum theory." (The author now regrets the extreme polemical tone of the book.)

This paper is about how to give human-like powers to complete agents. For this the most important design choice concerns the overall architecture. Questions regarding detailed mechanisms, forms of representations, inference capabilities, knowledge etc. are best addressed in the context of a global architecture in which different design decisions need to be linked. Such a design would assemble various kinds of functionality into a complete coherent working system, in which there are many concurrent, partly independent, partly mutually supportive, partly potentially incompatible processes, addressing a multitude of issues on different time scales, including asynchronous, concurrent, motive generators. Designing human like agents is part of the more general problem of understanding design space, niche space and their interrelations, for, in the abstract, there is no one optimal design, as biological diversity on earth shows

This paper offers a short and biased overview of the history of discussion and controversy about the role of different forms of representation in intelligent agents. It repeats and extends some of the criticisms of the `logicist' approach to AI that I first made in 1971, while also defending logic for its power and generality. It identifies some common confusions regarding the role of visual or diagrammatic reasoning including confusions based on the fact that different forms of representation may be used at different levels in an implementation hierarchy. This is contrasted with the way in the use of one form of representation (e.g. pictures) can be {\em controlled} using another (e.g. logic, or programs). Finally some questions are asked about the role of metrical information in biological visual systems.

This paper, along with the following paper by John McCarthy, introduces some of the topics to be discussed at the IJCAI95 event `A philosophical encounter: An interactive presentation of some of the key philosophical problems in AI and AI problems in philosophy.' Philosophy needs AI in order to make progress with many difficult questions about the nature of mind, and AI needs philosophy in order to help clarify goals, methods, and concepts and to help with several specific technical problems. Whilst philosophical attacks on AI continue to be welcomed by a significant subset of the general public, AI defenders need to learn how to avoid philosophically naive rebuttals