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We present a methodology for the automatic verification of multi-agent systems against temporal-epistemic specifications derived from higher-level languages defined over convergent equational theories. We introduce a modality called rewriting knowledge that o ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. Thisidentifica ...
The efficient synthesis of circuits is a well-studied problem. Due to the NP-hardness of the problem, no optimal algorithm has been presented so far. However, the heuristics presented by several researchers in the past, which are also adopted by commercial ...
Robots are both fascinating objects for the general public and devices whose conception, understanding and pro- gramming involve many fields. This unique combination makes them an ideal tool for introducing science and technology to children. This paper pr ...
Satisfiability modulo theory solvers are increasingly being used to solve quantified formulas over structures such as integers and term algebras. Quantifier instantiation combined with ground decision procedure alone is insufficient to prove many formulas ...
Implementing machine learning algorithms for large data, such as the Web graph and social networks, is challenging. Even though much research has focused on making sequential algorithms more scalable, their running times continue to be prohibitively long. ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
IT organizations that wish to implement the best practices recommended by the IT Infrastructure Library (ITIL) need to specify the level of service provided to their customers. The implemented service needs to comply with this specification. We propose a m ...
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinforcement learning problems. While utility bounds are known to exist for this ...
In this thesis, we explore the use of machine learning techniques for information retrieval. More specifically, we focus on ad-hoc retrieval, which is concerned with searching large corpora to identify the documents relevant to user queries. This identific ...
