66,465 research outputs found
Generating and Solving Symbolic Parity Games
We present a new tool for verification of modal mu-calculus formulae for
process specifications, based on symbolic parity games. It enhances an existing
method, that first encodes the problem to a Parameterised Boolean Equation
System (PBES) and then instantiates the PBES to a parity game. We improved the
translation from specification to PBES to preserve the structure of the
specification in the PBES, we extended LTSmin to instantiate PBESs to symbolic
parity games, and implemented the recursive parity game solving algorithm by
Zielonka for symbolic parity games. We use Multi-valued Decision Diagrams
(MDDs) to represent sets and relations, thus enabling the tools to deal with
very large systems. The transition relation is partitioned based on the
structure of the specification, which allows for efficient manipulation of the
MDDs. We performed two case studies on modular specifications, that demonstrate
that the new method has better time and memory performance than existing PBES
based tools and can be faster (but slightly less memory efficient) than the
symbolic model checker NuSMV.Comment: In Proceedings GRAPHITE 2014, arXiv:1407.767
Sparse Positional Strategies for Safety Games
We consider the problem of obtaining sparse positional strategies for safety
games. Such games are a commonly used model in many formal methods, as they
make the interaction of a system with its environment explicit. Often, a
winning strategy for one of the players is used as a certificate or as an
artefact for further processing in the application. Small such certificates,
i.e., strategies that can be written down very compactly, are typically
preferred. For safety games, we only need to consider positional strategies.
These map game positions of a player onto a move that is to be taken by the
player whenever the play enters that position. For representing positional
strategies compactly, a common goal is to minimize the number of positions for
which a winning player's move needs to be defined such that the game is still
won by the same player, without visiting a position with an undefined next
move. We call winning strategies in which the next move is defined for few of
the player's positions sparse.
Unfortunately, even roughly approximating the density of the sparsest
strategy for a safety game has been shown to be NP-hard. Thus, to obtain sparse
strategies in practice, one either has to apply some heuristics, or use some
exhaustive search technique, like ILP (integer linear programming) solving. In
this paper, we perform a comparative study of currently available methods to
obtain sparse winning strategies for the safety player in safety games. We
consider techniques from common knowledge, such as using ILP or SAT
(satisfiability) solving, and a novel technique based on iterative linear
programming. The results of this paper tell us if current techniques are
already scalable enough for practical use.Comment: In Proceedings SYNT 2012, arXiv:1207.055
Lex-Partitioning: A New Option for BDD Search
For the exploration of large state spaces, symbolic search using binary
decision diagrams (BDDs) can save huge amounts of memory and computation time.
State sets are represented and modified by accessing and manipulating their
characteristic functions. BDD partitioning is used to compute the image as the
disjunction of smaller subimages.
In this paper, we propose a novel BDD partitioning option. The partitioning
is lexicographical in the binary representation of the states contained in the
set that is represented by a BDD and uniform with respect to the number of
states represented. The motivation of controlling the state set sizes in the
partitioning is to eventually bridge the gap between explicit and symbolic
search.
Let n be the size of the binary state vector. We propose an O(n) ranking and
unranking scheme that supports negated edges and operates on top of precomputed
satcount values. For the uniform split of a BDD, we then use unranking to
provide paths along which we partition the BDDs. In a shared BDD representation
the efforts are O(n). The algorithms are fully integrated in the CUDD library
and evaluated in strongly solving general game playing benchmarks.Comment: In Proceedings GRAPHITE 2012, arXiv:1210.611
Synthesising Strategy Improvement and Recursive Algorithms for Solving 2.5 Player Parity Games
2.5 player parity games combine the challenges posed by 2.5 player
reachability games and the qualitative analysis of parity games. These two
types of problems are best approached with different types of algorithms:
strategy improvement algorithms for 2.5 player reachability games and recursive
algorithms for the qualitative analysis of parity games. We present a method
that - in contrast to existing techniques - tackles both aspects with the best
suited approach and works exclusively on the 2.5 player game itself. The
resulting technique is powerful enough to handle games with several million
states
Fully Observable Non-deterministic Planning as Assumption-Based Reactive Synthesis
We contribute to recent efforts in relating two approaches to automatic synthesis, namely, automated planning and discrete reactive synthesis. First, we develop a declarative characterization of the standard “fairness” assumption on environments in non-deterministic planning, and show that strong-cyclic plans are correct solution concepts for fair environments. This complements, and arguably completes, the existing foundational work on non-deterministic planning, which focuses on characterizing (and computing) plans enjoying special “structural” properties, namely loopy but closed policy structures. Second, we provide an encoding suitable for reactive synthesis that avoids the naive exponential state space blowup. To do so, special care has to be taken to specify the fairness assumption on the environment in a succinct manner.Fil: D'ippolito, Nicolás Roque. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Rodriguez, Natalia. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Sardina, Sebastian. RMIT University; Australi
Equilibria-based Probabilistic Model Checking for Concurrent Stochastic Games
Probabilistic model checking for stochastic games enables formal verification
of systems that comprise competing or collaborating entities operating in a
stochastic environment. Despite good progress in the area, existing approaches
focus on zero-sum goals and cannot reason about scenarios where entities are
endowed with different objectives. In this paper, we propose probabilistic
model checking techniques for concurrent stochastic games based on Nash
equilibria. We extend the temporal logic rPATL (probabilistic alternating-time
temporal logic with rewards) to allow reasoning about players with distinct
quantitative goals, which capture either the probability of an event occurring
or a reward measure. We present algorithms to synthesise strategies that are
subgame perfect social welfare optimal Nash equilibria, i.e., where there is no
incentive for any players to unilaterally change their strategy in any state of
the game, whilst the combined probabilities or rewards are maximised. We
implement our techniques in the PRISM-games tool and apply them to several case
studies, including network protocols and robot navigation, showing the benefits
compared to existing approaches
Model-Checking the Higher-Dimensional Modal mu-Calculus
The higher-dimensional modal mu-calculus is an extension of the mu-calculus
in which formulas are interpreted in tuples of states of a labeled transition
system. Every property that can be expressed in this logic can be checked in
polynomial time, and conversely every polynomial-time decidable problem that
has a bisimulation-invariant encoding into labeled transition systems can also
be defined in the higher-dimensional modal mu-calculus. We exemplify the latter
connection by giving several examples of decision problems which reduce to
model checking of the higher-dimensional modal mu-calculus for some fixed
formulas. This way generic model checking algorithms for the logic can then be
used via partial evaluation in order to obtain algorithms for theses problems
which may benefit from improvements that are well-established in the field of
program verification, namely on-the-fly and symbolic techniques. The aim of
this work is to extend such techniques to other fields as well, here
exemplarily done for process equivalences, automata theory, parsing, string
problems, and games.Comment: In Proceedings FICS 2012, arXiv:1202.317
Low-Effort Specification Debugging and Analysis
Reactive synthesis deals with the automated construction of implementations
of reactive systems from their specifications. To make the approach feasible in
practice, systems engineers need effective and efficient means of debugging
these specifications.
In this paper, we provide techniques for report-based specification
debugging, wherein salient properties of a specification are analyzed, and the
result presented to the user in the form of a report. This provides a
low-effort way to debug specifications, complementing high-effort techniques
including the simulation of synthesized implementations.
We demonstrate the usefulness of our report-based specification debugging
toolkit by providing examples in the context of generalized reactivity(1)
synthesis.Comment: In Proceedings SYNT 2014, arXiv:1407.493
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