30,509 research outputs found

    Topological Modelling of Grammatical and Lexical Aspect in English

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    It is assumed that aspect in both cases — as a process-profiling category — is analogous to the profiling of things and atemporal relations (in the sense of Langacker 1987, 1990, 2000), given the maximisation of the temporal domain in the characterisation of processes (perfective and imperfective, hence: dynamic and stative), and minimalisation of the temporal domain during the conceptualisation of things (conceptually independent entities) and atemporal relations (conceptually dependent atemporal configurations). The analogy between nouns and verbs in terms of ‘granularity’ has been so far variously addressed by Langacker (1990), Jackendoff (1991) and Talmy (2001), and also constitutes the core assumption in my research on topological modelling

    A Decentralized Mobile Computing Network for Multi-Robot Systems Operations

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    Collective animal behaviors are paradigmatic examples of fully decentralized operations involving complex collective computations such as collective turns in flocks of birds or collective harvesting by ants. These systems offer a unique source of inspiration for the development of fault-tolerant and self-healing multi-robot systems capable of operating in dynamic environments. Specifically, swarm robotics emerged and is significantly growing on these premises. However, to date, most swarm robotics systems reported in the literature involve basic computational tasks---averages and other algebraic operations. In this paper, we introduce a novel Collective computing framework based on the swarming paradigm, which exhibits the key innate features of swarms: robustness, scalability and flexibility. Unlike Edge computing, the proposed Collective computing framework is truly decentralized and does not require user intervention or additional servers to sustain its operations. This Collective computing framework is applied to the complex task of collective mapping, in which multiple robots aim at cooperatively map a large area. Our results confirm the effectiveness of the cooperative strategy, its robustness to the loss of multiple units, as well as its scalability. Furthermore, the topology of the interconnecting network is found to greatly influence the performance of the collective action.Comment: Accepted for Publication in Proc. 9th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conferenc

    An Extendable Multiagent Model for Behavioural Animation

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    This paper presents a framework for visually simulating the behaviour of actors in virtual environments. In principle, the environmental interaction follows a cyclic processing of perception, decision, and action. As natural life-forms perceive their environment by active sensing, our approach also tends to let the artificial actor actively sense the virtual world. This allows us to place the characters in non-preprocessed virtual dynamic environments, what we call generic environments. A main aspect within our framework is the strict distinction between a behaviour pattern, that we term model, and its instances, named characters, which use the pattern. This allows them sharing one or more behaviour models. Low-level tasks like sensing or acting are took over by so called subagents, which are subordinated modules extendedly plugged in the character. In a demonstration we exemplarily show the application of our framework. We place the same character in different environments and let it climb and descend stairs, ramps and hills autonomously. Additionally the reactiveness for moving objects is tested. In future, this approach shall go into action for a simulation of an urban environment

    Representation recovers information

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    Early agreement within cognitive science on the topic of representation has now given way to a combination of positions. Some question the significance of representation in cognition. Others continue to argue in favor, but the case has not been demonstrated in any formal way. The present paper sets out a framework in which the value of representation-use can be mathematically measured, albeit in a broadly sensory context rather than a specifically cognitive one. Key to the approach is the use of Bayesian networks for modeling the distal dimension of sensory processes. More relevant to cognitive science is the theoretical result obtained, which is that a certain type of representational architecture is *necessary* for achievement of sensory efficiency. While exhibiting few of the characteristics of traditional, symbolic encoding, this architecture corresponds quite closely to the forms of embedded representation now being explored in some embedded/embodied approaches. It becomes meaningful to view that type of representation-use as a form of information recovery. A formal basis then exists for viewing representation not so much as the substrate of reasoning and thought, but rather as a general medium for efficient, interpretive processing

    Action and behavior: a free-energy formulation

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    We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz’s agenda to understand the brain in terms of energy minimization. It is fairly easy to show that making inferences about the causes of sensory data can be cast as the minimization of a free-energy bound on the likelihood of sensory inputs, given an internal model of how they were caused. In this article, we consider what would happen if the data themselves were sampled to minimize this bound. It transpires that the ensuing active sampling or inference is mandated by ergodic arguments based on the very existence of adaptive agents. Furthermore, it accounts for many aspects of motor behavior; from retinal stabilization to goal-seeking. In particular, it suggests that motor control can be understood as fulfilling prior expectations about proprioceptive sensations. This formulation can explain why adaptive behavior emerges in biological agents and suggests a simple alternative to optimal control theory. We illustrate these points using simulations of oculomotor control and then apply to same principles to cued and goal-directed movements. In short, the free-energy formulation may provide an alternative perspective on the motor control that places it in an intimate relationship with perception

    Reasoning about representations in autonomous systems: what Pólya and Lakatos have to say

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