713 research outputs found
Two-Player Reachability-Price Games on Single-Clock Timed Automata
We study two player reachability-price games on single-clock timed automata.
The problem is as follows: given a state of the automaton, determine whether
the first player can guarantee reaching one of the designated goal locations.
If a goal location can be reached then we also want to compute the optimum
price of doing so. Our contribution is twofold. First, we develop a theory of
cost functions, which provide a comprehensive methodology for the analysis of
this problem. This theory allows us to establish our second contribution, an
EXPTIME algorithm for computing the optimum reachability price, which improves
the existing 3EXPTIME upper bound.Comment: In Proceedings QAPL 2011, arXiv:1107.074
IRBIT a Master Regulator of Cell Physiology
(excerpt)
Hormones and neurotransmitters regulate cell functions by binding to their receptors, which activate intracellular signaling and produce the physiological response [1]. There are several intracellular pathways, including but not limited to, leading to the activation of protein kinases, phosphatases and increase in intracellular calcium (Ca2+) [1]
Optimal Reachability in Divergent Weighted Timed Games
Weighted timed games are played by two players on a timed automaton equipped
with weights: one player wants to minimise the accumulated weight while
reaching a target, while the other has an opposite objective. Used in a
reactive synthesis perspective, this quantitative extension of timed games
allows one to measure the quality of controllers. Weighted timed games are
notoriously difficult and quickly undecidable, even when restricted to
non-negative weights. Decidability results exist for subclasses of one-clock
games, and for a subclass with non-negative weights defined by a semantical
restriction on the weights of cycles. In this work, we introduce the class of
divergent weighted timed games as a generalisation of this semantical
restriction to arbitrary weights. We show how to compute their optimal value,
yielding the first decidable class of weighted timed games with negative
weights and an arbitrary number of clocks. In addition, we prove that
divergence can be decided in polynomial space. Last, we prove that for untimed
games, this restriction yields a class of games for which the value can be
computed in polynomial time
Average-energy games
Two-player quantitative zero-sum games provide a natural framework to
synthesize controllers with performance guarantees for reactive systems within
an uncontrollable environment. Classical settings include mean-payoff games,
where the objective is to optimize the long-run average gain per action, and
energy games, where the system has to avoid running out of energy.
We study average-energy games, where the goal is to optimize the long-run
average of the accumulated energy. We show that this objective arises naturally
in several applications, and that it yields interesting connections with
previous concepts in the literature. We prove that deciding the winner in such
games is in NP inter coNP and at least as hard as solving mean-payoff games,
and we establish that memoryless strategies suffice to win. We also consider
the case where the system has to minimize the average-energy while maintaining
the accumulated energy within predefined bounds at all times: this corresponds
to operating with a finite-capacity storage for energy. We give results for
one-player and two-player games, and establish complexity bounds and memory
requirements.Comment: In Proceedings GandALF 2015, arXiv:1509.0685
Understanding the production of dual BEC with sympathetic cooling
We show, both experimentally and theoretically, that sympathetic cooling of
Rb atoms in the state by evaporatively cooled atoms in the
state can be precisely controlled to produce dual or single
condensate in either state. We also study the thermalization rate between two
species. Our model renders a quantitative account of the observed role of the
overlap between the two clouds and points out that sympathetic cooling becomes
inefficient when the masses are very different. Our calculation also yields an
analytical expression of the thermalization rate for a single species.Comment: 3 figure
Permissive Controller Synthesis for Probabilistic Systems
We propose novel controller synthesis techniques for probabilistic systems
modelled using stochastic two-player games: one player acts as a controller,
the second represents its environment, and probability is used to capture
uncertainty arising due to, for example, unreliable sensors or faulty system
components. Our aim is to generate robust controllers that are resilient to
unexpected system changes at runtime, and flexible enough to be adapted if
additional constraints need to be imposed. We develop a permissive controller
synthesis framework, which generates multi-strategies for the controller,
offering a choice of control actions to take at each time step. We formalise
the notion of permissivity using penalties, which are incurred each time a
possible control action is disallowed by a multi-strategy. Permissive
controller synthesis aims to generate a multi-strategy that minimises these
penalties, whilst guaranteeing the satisfaction of a specified system property.
We establish several key results about the optimality of multi-strategies and
the complexity of synthesising them. Then, we develop methods to perform
permissive controller synthesis using mixed integer linear programming and
illustrate their effectiveness on a selection of case studies
Verification and Control of Partially Observable Probabilistic Real-Time Systems
We propose automated techniques for the verification and control of
probabilistic real-time systems that are only partially observable. To formally
model such systems, we define an extension of probabilistic timed automata in
which local states are partially visible to an observer or controller. We give
a probabilistic temporal logic that can express a range of quantitative
properties of these models, relating to the probability of an event's
occurrence or the expected value of a reward measure. We then propose
techniques to either verify that such a property holds or to synthesise a
controller for the model which makes it true. Our approach is based on an
integer discretisation of the model's dense-time behaviour and a grid-based
abstraction of the uncountable belief space induced by partial observability.
The latter is necessarily approximate since the underlying problem is
undecidable, however we show how both lower and upper bounds on numerical
results can be generated. We illustrate the effectiveness of the approach by
implementing it in the PRISM model checker and applying it to several case
studies, from the domains of computer security and task scheduling
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