323,170 research outputs found
Autonomous cognitive systems in real-world environments: Less control, more flexibility and better interaction
In October 2011, the â2nd European Network for Cognitive Systems, Robotics and Interactionâ, EUCogII, held its meeting in Groningen on âAutonomous activity in real-world environmentsâ, organized by Tjeerd Andringa and myself. This is a brief personal report on why we thought autonomy in real-world environments is central for cognitive systems research and what I think I learned about it. --- The theses that crystallized are that a) autonomy is a relative property and a matter of degree, b) increasing autonomy of an artificial system from its makers and users is a necessary feature of increasingly intelligent systems that can deal with the real-world and c) more such autonomy means less control but at the same time improved interaction with the syste
An agent on my shoulder: AI, privacy and the application of human-like computing technologies to music creation
Human-Like Computing technologies are intelligent systems that interact with people in human-like way. By bringing together the disciplines of Artificial Intelligence, Ethnography and Interaction Design, and applying them in a real world context we are able to understand some of the ways that such technologies can be applied. This work in progress poster applies such technologies to the music creation and develops a design that is based on the notion of an âIntelligentâ Agent that is able to support in the music creation process
Non-local first-order modelling of crowd dynamics: a multidimensional framework with applications
In this work a physical modelling framework is presented, describing the
intelligent, non-local, and anisotropic behaviour of pedestrians. Its
phenomenological basics and constitutive elements are detailed, and a
qualitative analysis is provided. Within this common framework, two first-order
mathematical models, along with related numerical solution techniques, are
derived. The models are oriented to specific real world applications: a
one-dimensional model of crowd-structure interaction in footbridges and a
two-dimensional model of pedestrian flow in an underground station with several
obstacles and exits. The noticeable heterogeneity of the applications
demonstrates the significance of the physical framework and its versatility in
addressing different engineering problems. The results of the simulations point
out the key role played by the physiological and psychological features of
human perception on the overall crowd dynamics.Comment: 26 pages, 17 figure
Traffic3d:A rich 3D-traffic environment to train intelligent agents
The last few years marked a substantial development in the domain of Deep Reinforcement Learning. However, a crucial and not yet fully achieved objective is to devise intelligent agents which can be successfully taken out of the laboratory and employed in the real world. Intelligent agents that are successfully deployable in true physical settings, require substantial prior exposure to their intended environments. When this is not practical or possible, the agents benefit from being trained and tested on powerful test-beds, effectively replicating the real world. To achieve traffic management at an unprecedented level of efficiency, in this paper, we introduce a significantly richer new traffic simulation environment; Traffic3D. Traffic3D is a unique platform built to effectively simulate and evaluate a variety of 3D-road traffic scenarios, closely mimicking real-world traffic characteristics including faithful simulation of individual vehicle behavior, precise physics of movement and photo-realism. We discuss the merits of Traffic3D in comparison to state-of-the-art traffic-based simulators. Along with deep reinforcement learning, Traffic3D facilitates research across various domains such as object detection and segmentation, unsupervised representation learning, visual question answering, procedural generation, imitation learning and learning by interaction
The Development and Creation of Intelligent Systems in the next one hundred years
Today the intelligent systems are technological implemented as advanced machines [1] which have high perception, interaction and response to the real world being in much cases an extension of the reality, anticipating events,intertwining remote events, saving life and predicting preferences of human been [2,3] through of robust programming and electronic systems with high performance, optimization and design in operations where are required machines with an strong and complete interacting with the environment [2]; environment which also goes increasing until; in the very near future, to the ends of the Universe
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