Data Mining Practical Machine Learning Tools and Techniques

ing WS1S Systems to Verify Parameterized Networks . . . . . . . . . . . . 188 Kai Baukus, Saddek Bensalem, Yassine Lakhnech and Karsten Stahl FMona: A Tool for Expressing Validation Techniques over Infinite State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 J.-P. Bodeveix and M. Filali Transitive Closures of Regular Relations for Verifying Infinite-State Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Bengt Jonsson and Marcus Nilsson Diagnostic and Test Generation Using Static Analysis to Improve Automatic Test Generation . . . . . . . . . . . . . 235 Marius Bozga, Jean-Claude Fernandez and Lucian Ghirvu Efficient Diagnostic Generation for Boolean Equation Systems . . . . . . . . . . . . 251 Radu Mateescu Efficient Model-Checking Compositional State Space Generation with Partial Order Reductions for Asynchronous Communicating Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 266 Jean-Pierre Krimm and Laurent Mounier Checking for CFFD-Preorder with Tester Processes . . . . . . . . . . . . . . . . . . . . . . . 283 Juhana Helovuo and Antti Valmari Fair Bisimulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Thomas A. Henzinger and Sriram K. Rajamani Integrating Low Level Symmetries into Reachability Analysis . . . . . . . . . . . . . 315 Karsten Schmidt Model-Checking Tools Model Checking Support for the ASM High-Level Language . . . . . . . . . . . . . . 331 Giuseppe Del Castillo and Kirsten Winter Table of

Tools and Algorithms for the Construction and Analysis of Systems. Proc. TACAS 2009

Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariate data and the comparative lack of parametric models to represent it. Unfortunately, such exploration is also inherently more difficult.

Multivariate Density Estimation

This paper presents algorithms for the automatic synthesis of real-time controllers by finding a winning strategy for certain games defined by the timed-automata of Alur and Dill. In such games, the outcome depends on the players' actions as well as on their timing. We believe that these results will pave the way for the application of program synthesis techniques to the construction of real-time embedded systems from their specifications.

On the synthesis of discrete controllers for timed systems

Alternating-time temporal logic

We provide the first solution for model-free reinforcement learning of {\omega}-regular objectives for Markov decision processes (MDPs). We present a constructive reduction from the almost-sure satisfaction of {\omega}-regular objectives to an almost- sure reachability problem and extend this technique to learning how to control an unknown model so that the chance of satisfying the objective is maximized. A key feature of our technique is the compilation of {\omega}-regular properties into limit- deterministic Buechi automata instead of the traditional Rabin automata; this choice sidesteps difficulties that have marred previous proposals. Our approach allows us to apply model-free, off-the-shelf reinforcement learning algorithms to compute optimal strategies from the observations of the MDP. We present an experimental evaluation of our technique on benchmark learning problems.

Omega-Regular Objectives in Model-Free Reinforcement Learning

We provide the first solution for model-free reinforcement learning of \(\omega \)-regular objectives for Markov decision processes (MDPs). We present a constructive reduction from the almost-sure satisfaction of \(\omega \)-regular objectives to an almost-sure reachability problem, and extend this technique to learning how to control an unknown model so that the chance of satisfying the objective is maximized. We compile \(\omega \)-regular properties into limit-deterministic Buchi automata instead of the traditional Rabin automata; this choice sidesteps difficulties that have marred previous proposals. Our approach allows us to apply model-free, off-the-shelf reinforcement learning algorithms to compute optimal strategies from the observations of the MDP. We present an experimental evaluation of our technique on benchmark learning problems.

/pdf/omega-regular-objectives-in-model-free-reinforcement-428ssz1r5g.pdf

We study recursive timed automata that extend timed automata with recursion. Timed automata, as introduced by Alur and Dill, are finite automata accompanied by a finite set of real-valued variables called clocks. Recursive timed automata are finite collections of timed automata extended with special states that correspond to (potentially recursive) invocations of other timed automata from their collection. During an invocation of a timed automaton, our model permits passing the values of clocks using both pass-byvalue and pass-by-reference mechanisms. We study the natural reachability and termination (reachability with empty invocation stack) problems for recursive timed automata. We show that these problems are decidable (in many cases with the same complexity as the reachability problem on timed automata) for recursive timed automata satisfying the following condition: during each invocation either all clocks are passed by reference or none is passed by reference. Furthermore, we show that for recursive timed automata that violate this condition reachability/termination problems are undecidable for automata with as few as three clocks. We also establish similar results for two-player game extension of our model against reachability/termination objective.

http://qav.comlab.ox.ac.uk/papers/atva10.pdf

Recursive timed automata

In a reachability-time game, players Min and Max choose moves so that the time to reach a final state in a timed automaton is minimised or maximised, respectively. Asarin and Maler showed decidability of reachability-time games on strongly non-Zeno timed automata using a value iteration algorithm. This paper complements their work by providing a strategy improvement algorithm for the problem. It also generalizes their decidability result because the proposed strategy improvement algorithm solves reachability-time games on all timed automata. The exact computational complexity of solving reachability-time games is also established: the problem is EXPTIME-complete for timed automata with at least two clocks.

/pdf/reachability-time-games-on-timed-automata-2efuv6troh.pdf

Reachability-time games on timed automata

The theory of regular transformations of finite strings is quite mature with appealing properties. This class can be equivalently defined using both logic (Monadic second-order logic) and finite-state machines (two-way transducers, and more recently, streaming string transducers); is closed under operations such as sequential composition and regular choice; and problems such as functional equivalence and type checking, are decidable for this class. In this paper, we initiate a study of transformations of infinite strings. The MSO-based definition for regular string transformations generalizes naturally to infinite strings. We define an equivalent generalization of the machine model of streaming string transducers to infinite strings. A streaming string transducer is a deterministic machine that makes a single pass over the input string, and computes the output fragments using a finite set of string variables that are updated in a copyless manner at each step. We show how Muller acceptance condition for automata over infinite strings can be generalized to associate an infinite output string with an infinite execution. The proof that our model captures all MSO-definable transformations uses two-way transducers. Unlike the case of finite strings, MSO-equivalent definition of two-way transducers over infinite strings needs to make decisions based on omega-regular look-ahead. Simulating this look-ahead using multiple variables with copyless updates, is the main technical challenge in our constructions. Finally, we show that type checking and functional equivalence are decidable for MSO-definable transformations of infinite strings.

/pdf/regular-transformations-of-infinite-strings-t6dp43oig0.pdf

Ashutosh Trivedi

Papers

Omega-Regular Objectives in Model-Free Reinforcement Learning

Omega-Regular Objectives in Model-Free Reinforcement Learning

Recursive timed automata

Reachability-time games on timed automata

Regular Transformations of Infinite Strings