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Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using clas-sifiers and address policy learning as a supervised learning problem. This paper proposes variants of(More)
1 Introduction The open racing car simulator (TORCS [14]), is a modern, modular, highly-portable multi-player, multi-agent car simulator. Its high degree of modularity and portability render it ideal for artificial intelligence research. Indeed, a number of research-oriented competitions and papers have already appeared that make use of the TORCS engine.(More)
Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervised learning problem, have been proposed recently. Finding good policies with such methods requires not only an appropriate classifier, but also reliable examples for the best actions, covering(More)
The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number(More)
Intrusion detection is frequently used as a second line of defense in Mobile Ad-hoc Networks (MANETs). In this paper we examine how to properly use classification methods in intrusion detection for MANETs. In order to do so we evaluate five supervised classification algorithms for intrusion detection on a number of metrics. We measure their performance on a(More)
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or as different experts trying to solve the same task. Our main contribution is to formalise the problem as statistical preference elicitation, via a number of structured priors,(More)
HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt età la diffusion(More)
A number of authentication protocols have been proposed recently, where at least some part of the authentication is performed during a phase, lasting n rounds, with no error correction. This requires assigning an acceptable threshold for the number of detected errors. This paper describes a framework enabling an expected loss analysis for all the protocols(More)
Every day there are some 20 new cyber vulnerabilities released, each exposing some software weakness. For an information security manager it can be a daunting task to keep up and assess which vulnerabilities to prioritize to patch. In this thesis we use historic vulnerability data from the National Vulnerability Database (NVD) and the Exploit Database (EDB)(More)