5,170 research outputs found
Cellular automata approach to three-phase traffic theory
The cellular automata (CA) approach to traffic modeling is extended to allow
for spatially homogeneous steady state solutions that cover a two dimensional
region in the flow-density plane. Hence these models fulfill a basic postulate
of a three-phase traffic theory proposed by Kerner. This is achieved by a
synchronization distance, within which a vehicle always tries to adjust its
speed to the one of the vehicle in front. In the CA models presented, the
modelling of the free and safe speeds, the slow-to-start rules as well as some
contributions to noise are based on the ideas of the Nagel-Schreckenberg type
modelling. It is shown that the proposed CA models can be very transparent and
still reproduce the two main types of congested patterns (the general pattern
and the synchronized flow pattern) as well as their dependence on the flows
near an on-ramp, in qualitative agreement with the recently developed continuum
version of the three-phase traffic theory [B. S. Kerner and S. L. Klenov. 2002.
J. Phys. A: Math. Gen. 35, L31]. These features are qualitatively different
than in previously considered CA traffic models. The probability of the
breakdown phenomenon (i.e., of the phase transition from free flow to
synchronized flow) as function of the flow rate to the on-ramp and of the flow
rate on the road upstream of the on-ramp is investigated. The capacity drops at
the on-ramp which occur due to the formation of different congested patterns
are calculated.Comment: 55 pages, 24 figure
A Compositional Semantics for Stochastic Reo Connectors
In this paper we present a compositional semantics for the channel-based
coordination language Reo which enables the analysis of quality of service
(QoS) properties of service compositions. For this purpose, we annotate Reo
channels with stochastic delay rates and explicitly model data-arrival rates at
the boundary of a connector, to capture its interaction with the services that
comprise its environment. We propose Stochastic Reo automata as an extension of
Reo automata, in order to compositionally derive a QoS-aware semantics for Reo.
We further present a translation of Stochastic Reo automata to Continuous-Time
Markov Chains (CTMCs). This translation enables us to use third-party CTMC
verification tools to do an end-to-end performance analysis of service
compositions.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499
Complexity Measures from Interaction Structures
We evaluate new complexity measures on the symbolic dynamics of coupled tent
maps and cellular automata. These measures quantify complexity in terms of
-th order statistical dependencies that cannot be reduced to interactions
between units. We demonstrate that these measures are able to identify
complex dynamical regimes.Comment: 11 pages, figures improved, minor changes to the tex
HYPE with stochastic events
The process algebra HYPE was recently proposed as a fine-grained modelling
approach for capturing the behaviour of hybrid systems. In the original
proposal, each flow or influence affecting a variable is modelled separately
and the overall behaviour of the system then emerges as the composition of
these flows. The discrete behaviour of the system is captured by instantaneous
actions which might be urgent, taking effect as soon as some activation
condition is satisfied, or non-urgent meaning that they can tolerate some
(unknown) delay before happening. In this paper we refine the notion of
non-urgent actions, to make such actions governed by a probability
distribution. As a consequence of this we now give HYPE a semantics in terms of
Transition-Driven Stochastic Hybrid Automata, which are a subset of a general
class of stochastic processes termed Piecewise Deterministic Markov Processes.Comment: In Proceedings QAPL 2011, arXiv:1107.074
Limit Synchronization in Markov Decision Processes
Markov decision processes (MDP) are finite-state systems with both strategic
and probabilistic choices. After fixing a strategy, an MDP produces a sequence
of probability distributions over states. The sequence is eventually
synchronizing if the probability mass accumulates in a single state, possibly
in the limit. Precisely, for 0 <= p <= 1 the sequence is p-synchronizing if a
probability distribution in the sequence assigns probability at least p to some
state, and we distinguish three synchronization modes: (i) sure winning if
there exists a strategy that produces a 1-synchronizing sequence; (ii)
almost-sure winning if there exists a strategy that produces a sequence that
is, for all epsilon > 0, a (1-epsilon)-synchronizing sequence; (iii) limit-sure
winning if for all epsilon > 0, there exists a strategy that produces a
(1-epsilon)-synchronizing sequence.
We consider the problem of deciding whether an MDP is sure, almost-sure,
limit-sure winning, and we establish the decidability and optimal complexity
for all modes, as well as the memory requirements for winning strategies. Our
main contributions are as follows: (a) for each winning modes we present
characterizations that give a PSPACE complexity for the decision problems, and
we establish matching PSPACE lower bounds; (b) we show that for sure winning
strategies, exponential memory is sufficient and may be necessary, and that in
general infinite memory is necessary for almost-sure winning, and unbounded
memory is necessary for limit-sure winning; (c) along with our results, we
establish new complexity results for alternating finite automata over a
one-letter alphabet
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