63 research outputs found

    Strengthening Model Checking Techniques with Inductive Invariants

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    This paper describes optimized techniques to efficiently compute and reap benefits from inductive invariants within SAT-based model checking. We address sequential circuit verification, and we consider both equivalences and implications between pairs of nodes in the logic networks. First, we present a very efficient dynamic procedure, based on equivalence classes and incremental SAT, specifically oriented to reduce the set of checked invariants. Then, we show how to effectively integrate the computation of inductive invariants within state-of-the-art SAT-based model checking procedures. Experiments (on more than 600 designs) show the robustness of our approach on verification instances on which stand-alone techniques fai

    Applying Formal Methods to Networking: Theory, Techniques and Applications

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    Despite its great importance, modern network infrastructure is remarkable for the lack of rigor in its engineering. The Internet which began as a research experiment was never designed to handle the users and applications it hosts today. The lack of formalization of the Internet architecture meant limited abstractions and modularity, especially for the control and management planes, thus requiring for every new need a new protocol built from scratch. This led to an unwieldy ossified Internet architecture resistant to any attempts at formal verification, and an Internet culture where expediency and pragmatism are favored over formal correctness. Fortunately, recent work in the space of clean slate Internet design---especially, the software defined networking (SDN) paradigm---offers the Internet community another chance to develop the right kind of architecture and abstractions. This has also led to a great resurgence in interest of applying formal methods to specification, verification, and synthesis of networking protocols and applications. In this paper, we present a self-contained tutorial of the formidable amount of work that has been done in formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial

    A Quantitative Analysis of Memory Usage for Agent Tasks

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    Reachability analysis using partitioned-ROBDDs

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    Improved Symbolic Model Checking of Real-Time Systems

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    Ph.DDOCTOR OF PHILOSOPH

    Worst-case temporal analysis of real-time dynamic streaming applications

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    Goal-oriented Behaviour for Intelligent Game Agents

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    This thesis concerns our innovation in game AI techniques, mainly game agents' modeling, planning and learning. The research topic involves the development of a game design software --- Gameme. Our work mainly focus on the development of the core AI module. In this thesis, after discussing the system design of Gameme, we explain our contributions in two parts: off-line design and real-time processing. In off-line design, we present goal-oriented behaviour design and related modeling methodology for game agents. The goal-oriented design provides not only an intuitive behaviour design methodology for non-professional game designers but also efficient support for real-time behaviour control. In particular, the goal-oriented design can be used in modeling agents in different games. The real-time processing component includes planning and learning mechanisms for game agents. These mechanisms are placed in a layered architecture. Basically, a procedural planning mechanism allows game agents to have the ability of fast reaction to their environment. Then, the creative transfer and adaptive learning mechanism trains game agents to learn from their experience and cooperate in teamwork. Furthermore, the unique emergent learning mechanism can allow game agents to have the ability to analyze different PCs' behaviour patterns and to find the suitable strategy to defeat PCs in real-time. Most of the experiments in this thesis are performed in fighting scenarios. We connected the core AI module with a 3D graphics engine in order to have visual testing results. All test cases show that our goal-oriented behaviour design along with planning and learning mechanisms can provide fast, autonomous, collaborative and adaptive behaviour instructions for game agent in real-time game play
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