Searched for: author%3A%22Witteveen%2C+C.%22
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Noroozian, A. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
The fundamental problem with P2P networks is that quality of service depends on altruistic resource sharing by participating peers. Many peers freeride on the generosity of others. Current solutions like sharing ratio enforcement and reputation systems are complex, exploitable, inaccurate or unfair at times. The need to design scalable...
conference paper 2012
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
We develop a novel learning algorithm RTI for identifying a deterministic real-time automaton (DRTA) from labeled time-stamped event sequences. The RTI algorithm is based on the current state of the art in deterministic finite-state automaton (DFA) identification, called evidence-driven state-merging (EDSM). In addition to having a DFA structure...
journal article 2011
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
We advocate the use of an explicit time representation in syntactic pattern recognition because it can result in more succinct models and easier learning problems. We apply this approach to the real-world problem of learning models for the driving behavior of truck drivers. We discretize the values of onboard sensors into simple events. Instead...
conference paper 2011
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Zutt, J. (author), Van Gemund, A.J.C. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
An important problem in transportation is how to ensure efficient operational route planning when several vehicles share a common road infrastructure with limited capacity. Examples of such a problem are route planning for automated guided vehicles in a terminal and route planning for aircraft taxiing at airports. Maintaining efficiency in such...
book chapter 2010
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Verwer, S. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
We develop theory on the efficiency of identifying (learning) timed automata. In particular, we show that: (i) deterministic timed automata cannot be identified efficiently in the limit from labeled data and (ii) that one-clock deterministic timed automata can be identified efficiently in the limit from labeled data. We prove these results based...
journal article 2010
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Verwer, S. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
conference paper 2010
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Planken, L.R. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
When agents need to interact in order to solve some (possibly common) problem, resolving potential conflicts beforehand is often preferred to coordination during execution. Agents may lose some flexibility, but their course of action will be more predictable and often also more efficient, obtaining a socially optimal outcome instead of a local...
conference paper 2010
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Wu, M. (author), De Weerdt, M.M. (author), La Poutré, H. (author), Yadati, C. (author), Zhang, Y. (author), Witteveen, C. (author)
conference paper 2009
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Stranders, R. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
In an open Multi-Agent System, the goals of agents acting on behalf of their owners often conflict with each other. Therefore, a personal agent protecting the interest of a single user cannot always rely on them. Consequently, such a personal agent needs to be able to reason about trusting (information or services provided by) other agents....
book chapter 2008
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Verwer, S. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
conference paper 2008
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
We describe an efficient algorithm for learning deterministic real-time automata (DRTA) from positive data. This data can be obtained from observations of the process to be modeled. The DRTA model we learn from such data can be used reason and gain knowledge about realtime systems such as network protocols, business processes, reactive systems,...
conference paper 2008
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
This paper describes an efficient algorithm for learning a timed model from observations. The algorithm is based on the state merging method for learning a deterministic finite state automaton (DFA). This method and its problem have been the subject of many studies within the grammatical inference field, see e.g. (de la Higuera, 2005)....
conference paper 2008
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
A common model for discrete event systems is a deterministic finite automaton (DFA). An advantage of this model is that it can be interpreted by domain experts. When observing a real-world system, however, there often is more information than just the sequence of discrete events: the time at which these events occur may be very important. In...
conference paper 2007
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe state-merging algorithm for the problem of learning...
conference paper 2007
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Steenhuisen, J.R. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
In crisis response, hierarchical organizations are being replaced by dynamic assemblies of autonomous agents that promise more agility. However, these autonomous agents might cause a decrease in effectiveness when individually constructed plans for moderately-coupled tasks are not jointly feasible. Existing coordination techniques can be applied...
conference paper 2007
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
We are interested in identifying a model for discrete event systems from observations. A common way to model discrete event systems is by using deterministic finite state automata (DFA). When observing a system, however, there often is information in addition to the system events, namely, their times of occurrence. If this time information is...
conference paper 2006
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
In our paper we focus on learning systems of which the execution is determined by a finite set of discrete events. The full version of this paper appeared in: Proceedings of the 15th Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn 2006): http://resolver.tudelft.nl/uuid:faab7982-46bf-4d52-8a2a-324a88542584
conference paper 2006
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Verwer, S.E. (author), De Weerdt, M.M. (author), Witteveen, C. (author)
A model for discrete event systems (DES) can be learned from observations. We propose a simple type of timed automaton to model DES where the timing of the events is important. Learning such an automaton is proven to be NP-complete by a reduction from the problem of learning deterministic finite state automata (DFA) without time. Based on this...
conference paper 2006
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De Weerdt, M.M. (author), Witteveen, C. (author)
Many different problems are called distributed or multiagent planning problems. Existing approaches each deal with only a subset of these problems. Which properties are essential in determining a solution method for multiagent planning problems? We argue that mainly the facts that communication is limited, agents have private goals, and the...
conference paper 2006
document
Witteveen, C. (author), De Weerdt, M.M. (author)
conference paper 2006
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