The possibility of interacting with remote services in natural language opens up new opportunities for sharing knowledge and for automating services. Easy-to-use, text-based interfaces might provide more democratic ac...
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ISBN:
(纸本)9783902823205
The possibility of interacting with remote services in natural language opens up new opportunities for sharing knowledge and for automating services. Easy-to-use, text-based interfaces might provide more democratic access to legal information, government services, and everyday knowledge as well. However, the methodology of engineering robust natural language interfaces is very diverse and widely deployed solutions are still yet to come. In this paper the author offers a theoretical insight that might provide useful as a common ground for discussion. The main contribution is a detailed problem analysis, which reveals that a text-based interface is best understood as an artificial agent that represents the interests of the remote party who is separated in time and space from the client. A possible ethical issue about the development of such an agent is also discussed.
The possibility of interacting with remote services in natural language opens up new opportunities for sharing knowledge and for automating services. Easy-to-use, text-based interfaces might provide more democratic ac...
详细信息
The possibility of interacting with remote services in natural language opens up new opportunities for sharing knowledge and for automating services. Easy-to-use, text-based interfaces might provide more democratic access to legal information, government services, and everyday knowledge as well. However, the methodology of engineering robust natural language interfaces is very diverse and widely deployed solutions are still yet to come. In this paper the author offers a theoretical insight that might provide useful as a common ground for discussion. The main contribution is a detailed problem analysis, which reveals that a text-based interface is best understood as an artificial agent that represents the interests of the remote party who is separated in time and space from the client. A possible ethical issue about the development of such an agent is also discussed.
Business intelligence, e-science and Web mining are rapidly growing sources of extreme large scale problems. We demonstrate that emerging means of supercomputing-for-the-masses, distributed or many-core architectures ...
Business intelligence, e-science and Web mining are rapidly growing sources of extreme large scale problems. We demonstrate that emerging means of supercomputing-for-the-masses, distributed or many-core architectures may provide feasible and affordable solution to many applications. We give a brief overview in four areas: • Web data processing to federate Future Internet Research (FIRE) facilities in a recently started project; • Image retrieval over tasks of the PASCAL and PROMISE networks of excellence; • Efficiency of distributed data warehouses for log processing and entity resolution; • Network analysis, visualization and navigation, in the VAST Challenges and European security projects. We pass beyond existing technologies in implementing new frameworks, combining distributed and multicore technologies, and seeking new, breakthrough applications in an interdisciplinary research with application partners.
作者：
János NacsaImre PanitiSándor KopácsiCIM Laboratory
MTA SZTAKI Institute for Computer Science and Control Hungarian Academy of Sciences (ATOMKI) Budapest Hungary MTA SZTAKI
Department of MOGI Mechatronics Optics and Engineering Informatics Budapest University슠of슠Technology슠and슠Economics Hungary MTA SZTAKI
Dennis Gabor College Hungary
Incremental Sheet Forming is an advanced manufacturing technology in the recent years. In a lot of cases the process requires the synchronized cooperation of two machines. The complex operation was modelled in a virtu...
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Incremental Sheet Forming is an advanced manufacturing technology in the recent years. In a lot of cases the process requires the synchronized cooperation of two machines. The complex operation was modelled in a virtual environment, where the cyber objects were deeply connected with the real objects. The result of this virtual cooperation resulted some cognitive observation that is also published in this paper.
To manage and monitor their networks in a proper way, network operators are often interested in identifying the applications generating the traffic traveling through their networks, and doing it as fast (i.e., from as...
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To manage and monitor their networks in a proper way, network operators are often interested in identifying the applications generating the traffic traveling through their networks, and doing it as fast (i.e., from as few packets) as possible. State-of-the-art packet-based traffic classification methods are either based on the costly inspection of the payload of several packets of each flow or on basic flow statistics that do not take into account the packet content. In this paper we consider the intermediate approach of analyzing only the first few bytes of the first (or first few) packets of each flow. We propose automatic, machine-learning-based methods achieving remarkably good early classification performance on real traffic traces generated from a diverse set of applications (including several versions of P2P TV and file sharing), while requiring only limited computational and memory resources.
We consider online learning in finite stochastic Markovian environments where in each time step a new reward function is chosen by an oblivious adversary. The goal of the learning agent is to compete with the best sta...
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ISBN:
(纸本)9781617823800
We consider online learning in finite stochastic Markovian environments where in each time step a new reward function is chosen by an oblivious adversary. The goal of the learning agent is to compete with the best stationary policy in terms of the total reward received. In each time step the agent observes the current state and the reward associated with the last transition, however, the agent does not observe the rewards associated with other state-action pairs. The agent is assumed to know the transition probabilities. The state of the art result for this setting is a no-regret algorithm. In this paper we propose a new learning algorithm and, assuming that stationary policies mix uniformly fast, we show that after T time steps, the expected regret of the new algorithm is O (T2/3(ln T)1/3 ), giving the first rigorously proved regret bound for the problem.
We consider online learning in finite stochastic Markovian environments where in each time step a new reward function is chosen by an oblivious adversary. The goal of the learning agent is to compete with the best sta...
We consider online learning in finite stochastic Markovian environments where in each time step a new reward function is chosen by an oblivious adversary. The goal of the learning agent is to compete with the best stationary policy in terms of the total reward received. In each time step the agent observes the current state and the reward associated with the last transition, however, the agent does not observe the rewards associated with other state-action pairs. The agent is assumed to know the transition probabilities. The state of the art result for this setting is a no-regret algorithm. In this paper we propose a new learning algorithm and, assuming that stationary policies mix uniformly fast, we show that after T time steps, the expected regret of the new algorithm is O (T2/3 (ln T)1/3), giving the first rigorously proved regret bound for the problem.
This book provides a comprehensive overview of active anti-roll bar systems on heavy vehicles as one of the most effective solutions for improving the roll stability of these vehicles. Due to the characteristics of th...
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ISBN:
(数字)9789819713592
ISBN:
(纸本)9789819713585;9789819713615
This book provides a comprehensive overview of active anti-roll bar systems on heavy vehicles as one of the most effective solutions for improving the roll stability of these vehicles. Due to the characteristics of these vehicles with heavy loads and high center of gravity, the possibility of roll instability occurs frequently and causes serious consequences for human life, vehicles, and traffic infrastructure. The book gives readers an in-depth survey of the roll instability characteristics of heavy vehicles such as single-unit trucks with rigid and flexible frames, and tractor semi-trailers. It then introduces an active anti-roll bar system, the electro-hydraulic actuators which use control methods such as LQR optimal and H∞ robust controller design. This work introduces a new control method, which is a combination of robust control with the linear parameter varying system (H∞/LPV). The validation of the new hybrid method is carried out using the nonlinear truck model from the TruckSim® software to assess the roll stability of heavy vehicles in order to limit the rollover accident. A number of examples are provided to illustrate the research results, which helps the readers have a practical and easy approach that can be applied to other active anti-roll bar systems for most forms of transport vehicles in general. This book caters to academics and practitioners who are interested in active anti-roll bar systems for the typical heavy vehicle available worldwide.
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