Innate theories as a basis for autonomous mental development

technical reportSloman (in robotics), Chomsky and Pinker (in natural language), and others, e.g., Rosenberg (in human cooperative behavior) have proposed that some abstract theories relevant to cognitive activity are encoded genetically in humans. The biological advantages of this are (1) to reduce the learning time for acquisition of speci c contextual models (e.g., from a language community; appropriate physics, etc.), and (2) to allow the determination of true statements about the world beyond those immediately available from direct experience. We believe that this hypothesis is a strong paradigm for the autonomous mental development of arti cial cognitive agents and we give speci c examples and propose a theoretical and experimental framework for this. In particular, we show that knowledge and exploitation of symmetry can lead to greatly reduced reinforcement learning times on a selected set of problems

Symmetry as an organizational principle in cognitive sensor networks

technical reportCognitive sensor networks are able to perceive, learn, reason and act by means of a distributed, sensor/actuator, computation and communication system. In animals, cognitive capabilities do not arise from a tabula rasa, but are due in large part to the intrinsic architecture (genetics) of the animal which has been evolved over a long period of time and depends on a combination of constraints: e.g., ingest nutrients, avoid toxins, etc. We have previously shown how organism morphology arises from genetic algorithms responding to such constraints[6]. Recently, it has been suggested that abstract theories relevant to speci c cognitive domains are likewise genetically coded in humans (e.g., language, physics of motion, logic, etc.); thus, these theories and models are abstracted from experience over time. We call this the Domain Theory Hypothesis, and other proponents include Chomsky [2] and Pinker [11] (universal language), Sloman [16, 17] (arti cial intelligence), and Rosenberg [13] (cooperative behavior). Some advantages of such embedded theories are that they (1) make learning more ef cient, (2) allow generalization across models, and (3) allow determination of true statements about the world beyond those available from direct experience. We have shown in previous work how theories of symmetry can dramatically improve representational ef ciency and aid reinforcement learning on various problems [14]. However, it remains to be shown sensory data can be organized into appropriate elements so as to produce a model of a given theory. We address this here by showing how symmetric elements can be perceived by a sensor network and the role this plays in a cognitive system's ability to discover knowledge about its own structure as well as about the surrounding physical world. Our view is that cognitive sensor networks which can learn these things will not need to be pre-programmed in detail for specific tasks

FOR WORKSHOP: THE INCOMPUTABLE,

of virtual machinery with “physically indefinable ” functions What’s Meta-Morphogenesis? A partial answer: Evolution, individual development, learning, and cultural change producing new mechanisms of evolution, individual development, learning, and cultural chang

Natural minds: maps, mental causation and virtual machines

My project is an empirically informed investigation of the philosophical problem of mental causation, and simultaneously a philosophical investigation of the status of cognitive scientific generalisations. If there is such a thing as mental causation, that is, mental states having effects qua mental states, and if we can classify the mental states involved in these causes in a way useful for making predictions and giving scientific explanations, then these states will be natural kinds. The first task, then, is to show that there is an account of natural kindhood that can accommodate cognitive kinds. The second task is to say how the scientific statements made using these mental kinds are not susceptible to being reduced to statements about physical kinds, and in fact require taking into account facts at many levels of explanation, including the biological and social levels. Lastly, the case will be made for Virtual Machine Functionalism being the correct account of the relationship between cognitive states and the broader physical world. I will claim that although there may be problems with traditional accounts of natural kinds and mental representations when it comes to contemporary cognitive science, this is no reason for thinking that those terms are not useful; we should refine rather than eliminate them. Something would be lost in our understanding if we rejected these terms and the theoretical understanding they contain, something that was present before some mistaken theoretical details came to be associated with the terms. Perhaps some terms that have been coined in the development of our understanding of the mind, such as ‘qualia,’ should be dispensed with, but others just need to be cleaned up. Broadly speaking, my argument will be that squaring the widely held but somewhat contradictory intuitions of physicalism and anti-reductionism regarding mental states will require modification of two other commonly held intuitions, namely physical causal closure and supervenience. Another way of stating my aim is in terms of defending the intuitive distinction between metaphorical and literal uses of intentional vocabulary, such as ‘wanting’ and ‘trying,’ against those who question the meaningfulness of this distinction because they take a physicalist stance on questions of consciousness. They may say the distinction is merely verbal, that there is no real difference between saying of a raindrop that it is ‘trying’ to get to the bottom of the window pane, and saying of a person that he or she is trying to get to the top of the mountain. Much of what follows is an attempt to describe a metaphysics that is materialist and scientific, but in which the difference between the two cases has a natural place. 4 The difference lies in the idea of intentionality: in the case of my desiring something, there is a mental state ‘in’ me that is there because it has the function of directing my actions towards bringing about the desired state of affairs. Such states are things that can be scientifically studied, and a scientific account of human action would be incomplete if it did not refer to such states. In the case of the water drop, there are no similar states without which the scientific understanding of water droplet action would be incomplete. The temptation to elide the distinction between intentional and non-intentional descriptions is based on a belief that since all causation is physical, there is no meaningful distinction between the kinds of causes that makes water drops drop, and those that make climbers climb. This results from the fact that it is sometimes felt that reference to such things as personal agency in intentional explanations of action is to allow in a disagreeable form of dualism. I will argue that a complete, physicalistic, scientific account of human behaviour must include reference to irreducible, mental kinds, such as beliefs and desires. The form of the argument follows the content, with natural kinds at the centre of the web of concepts that form our understanding of mind and its place in the natural world. The starting point is simple folk explanations of human actions, like, ‘He ate the apple because…’ followed by a set of conditions including combinations of beliefs and desires that together constitute sufficient reasons for eating the apple. Many would say such purported explanations are fictions that mask our ignorance of the true story, which will, when we know how to tell it, have a reduced cast of characters, an exclusive set of ‘purely’ physical types. This is well-trodden ground, onto which defenders of ‘embodied cognitive science’ have stepped. However, it is not clear who they will side with, whether they could tip the balance one way or the other, or indeed whether they will even be a unified force. A ‘topographical’ account of natural kinds will be developed that avoids problems other accounts face, and which is suitable for use in the general statements constructed in embodied cognitive science. Following that, we will use this account in the debate around the autonomy of special sciences in general, and the problem of mental causation in particular. The discussion will then broaden out into an investigation of causation, including a refined understanding of physical causal closure. After applying the results of these discussions to our understanding of the supervenience relation, a defensible account of emergentism will be given. Next, we will look at the kinds of properties of mental states that may be referred to in explanations of rational action, namely, the ¬representational contents of mental states. In order to understand the nature of these states, the feedback dynamics between hierarchically structured levels of cognition involved in their evolution will be foregrounded, leading to a picture of embodied cognition that is broad and externalist. We will then look at experiential 5 properties, showing them to be an inseparable part of intentional states, and describing how subjecthood is emergent from brain/body/world dynamics. We will finish by outlining the implications of the refined functionalist account defended for the metaphysical notions we started with. The conclusion drawn will be that we can indeed refer to genuine mental causes which ground the non-metaphorical use of intentional explanations. Finally, I will sketch some implications for the idea of free will using empirical landmarks from cognitive science to find a path through the eroded philosophical landscape, while at the same time using these old philosophical waymarkers to guide the scientific exploration of cognition ahead of us

The Well-designed Young Mathematician

AbstractThis paper complements McCarthy's “The well designed child”, in part by putting it in a broader context, a space of sets of requirements and a space of designs, and in part by relating design features to development of mathematical competences. I moved into AI hoping to understand myself, especially hoping to understand how I could do mathematics. Over the ensuing four decades, my interactions with AI and other disciplines led to: design-based, cross-disciplinary investigations of requirements, especial those arising from interactions with a complex environment; a draft partial ontology for describing spaces of possible architectures, especially virtual machine architectures; investigations of how different forms of representation relate to different functions; analysis of biological nature/nurture tradeoffs and their relevance to machines; studies of control issues in a complex architecture; and showing how what can occur in such an architecture relates to our intuitive concepts of motivation, feeling, preferences, emotions, attitudes, values, moods, consciousness, etc. I conjecture that working models of human vision can lead to models of spatial reasoning that would help to support Kant's view of mathematics by showing that human mathematical abilities are a natural extension of abilities produced by biological evolution that are not yet properly understood, and have barely been noticed by psychologists and neuroscientists. Some requirements for such models, are described, including aspects of our ability to interact with complex 3-D structures and processes that extend Gibson's ideas concerning action affordances, to include proto-affordances, epistemic affordances and deliberative affordances. Some of what a child learns about structures and processes starts as empirical then, as a result of reflective processes, can be recognised as necessary (e.g., mathematical) truths. These processes normally develop unnoticed in young children, but provide the basis for much creativity in behaviour, as well as leading, in some, to development of an interest in mathematics. We still need to understand what sort of self-monitoring and self-extending architecture, and what forms of representation, are required to make this possible. This paper does not presuppose that all mathematical learners can do logic, though some fairly general form of reasoning seems to be required