671 research outputs found
Extension of PRISM by Synthesis of Optimal Timeouts in Fixed-Delay CTMC
We present a practically appealing extension of the probabilistic model
checker PRISM rendering it to handle fixed-delay continuous-time Markov chains
(fdCTMCs) with rewards, the equivalent formalism to the deterministic and
stochastic Petri nets (DSPNs). fdCTMCs allow transitions with fixed-delays (or
timeouts) on top of the traditional transitions with exponential rates. Our
extension supports an evaluation of expected reward until reaching a given set
of target states. The main contribution is that, considering the fixed-delays
as parameters, we implemented a synthesis algorithm that computes the
epsilon-optimal values of the fixed-delays minimizing the expected reward. We
provide a performance evaluation of the synthesis on practical examples
Probabilistic Timed Automata with Clock-Dependent Probabilities
Probabilistic timed automata are classical timed automata extended with
discrete probability distributions over edges. We introduce clock-dependent
probabilistic timed automata, a variant of probabilistic timed automata in
which transition probabilities can depend linearly on clock values.
Clock-dependent probabilistic timed automata allow the modelling of a
continuous relationship between time passage and the likelihood of system
events. We show that the problem of deciding whether the maximum probability of
reaching a certain location is above a threshold is undecidable for
clock-dependent probabilistic timed automata. On the other hand, we show that
the maximum and minimum probability of reaching a certain location in
clock-dependent probabilistic timed automata can be approximated using a
region-graph-based approach.Comment: Full version of a paper published at RP 201
More than a feeling: A unified view of stress measurement for population science.
Stress can influence health throughout the lifespan, yet there is little agreement about what types and aspects of stress matter most for human health and disease. This is in part because "stress" is not a monolithic concept but rather, an emergent process that involves interactions between individual and environmental factors, historical and current events, allostatic states, and psychological and physiological reactivity. Many of these processes alone have been labeled as "stress." Stress science would be further advanced if researchers adopted a common conceptual model that incorporates epidemiological, affective, and psychophysiological perspectives, with more precise language for describing stress measures. We articulate an integrative working model, highlighting how stressor exposures across the life course influence habitual responding and stress reactivity, and how health behaviors interact with stress. We offer a Stress Typology articulating timescales for stress measurement - acute, event-based, daily, and chronic - and more precise language for dimensions of stress measurement
The Emergence of Norms via Contextual Agreements in Open Societies
This paper explores the emergence of norms in agents' societies when agents
play multiple -even incompatible- roles in their social contexts
simultaneously, and have limited interaction ranges. Specifically, this article
proposes two reinforcement learning methods for agents to compute agreements on
strategies for using common resources to perform joint tasks. The computation
of norms by considering agents' playing multiple roles in their social contexts
has not been studied before. To make the problem even more realistic for open
societies, we do not assume that agents share knowledge on their common
resources. So, they have to compute semantic agreements towards performing
their joint actions. %The paper reports on an empirical study of whether and
how efficiently societies of agents converge to norms, exploring the proposed
social learning processes w.r.t. different society sizes, and the ways agents
are connected. The results reported are very encouraging, regarding the speed
of the learning process as well as the convergence rate, even in quite complex
settings
Chronic psychosocial and financial burden accelerates 5-year telomere shortening: findings from the Coronary Artery Risk Development in Young Adults Study.
Leukocyte telomere length, a marker of immune system function, is sensitive to exposures such as psychosocial stressors and health-maintaining behaviors. Past research has determined that stress experienced in adulthood is associated with shorter telomere length, but is limited to mostly cross-sectional reports. We test whether repeated reports of chronic psychosocial and financial burden is associated with telomere length change over a 5-year period (years 15 and 20) from 969 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) Study, a longitudinal, population-based cohort, ages 18-30 at time of recruitment in 1985. We further examine whether multisystem resiliency, comprised of social connections, health-maintaining behaviors, and psychological resources, mitigates the effects of repeated burden on telomere attrition over 5 years. Our results indicate that adults with high chronic burden do not show decreased telomere length over the 5-year period. However, these effects do vary by level of resiliency, as regression results revealed a significant interaction between chronic burden and multisystem resiliency. For individuals with high repeated chronic burden and low multisystem resiliency (1 SD below the mean), there was a significant 5-year shortening in telomere length, whereas no significant relationships between chronic burden and attrition were evident for those at moderate and higher levels of resiliency. These effects apply similarly across the three components of resiliency. Results imply that interventions should focus on establishing strong social connections, psychological resources, and health-maintaining behaviors when attempting to ameliorate stress-related decline in telomere length among at-risk individuals
Synchronization and Control in Intrinsic and Designed Computation: An Information-Theoretic Analysis of Competing Models of Stochastic Computation
We adapt tools from information theory to analyze how an observer comes to
synchronize with the hidden states of a finitary, stationary stochastic
process. We show that synchronization is determined by both the process's
internal organization and by an observer's model of it. We analyze these
components using the convergence of state-block and block-state entropies,
comparing them to the previously known convergence properties of the Shannon
block entropy. Along the way, we introduce a hierarchy of information
quantifiers as derivatives and integrals of these entropies, which parallels a
similar hierarchy introduced for block entropy. We also draw out the duality
between synchronization properties and a process's controllability. The tools
lead to a new classification of a process's alternative representations in
terms of minimality, synchronizability, and unifilarity.Comment: 25 pages, 13 figures, 1 tabl
"How May I Help You?": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts
Given the increasing popularity of customer service dialogue on Twitter,
analysis of conversation data is essential to understand trends in customer and
agent behavior for the purpose of automating customer service interactions. In
this work, we develop a novel taxonomy of fine-grained "dialogue acts"
frequently observed in customer service, showcasing acts that are more suited
to the domain than the more generic existing taxonomies. Using a sequential
SVM-HMM model, we model conversation flow, predicting the dialogue act of a
given turn in real-time. We characterize differences between customer and agent
behavior in Twitter customer service conversations, and investigate the effect
of testing our system on different customer service industries. Finally, we use
a data-driven approach to predict important conversation outcomes: customer
satisfaction, customer frustration, and overall problem resolution. We show
that the type and location of certain dialogue acts in a conversation have a
significant effect on the probability of desirable and undesirable outcomes,
and present actionable rules based on our findings. The patterns and rules we
derive can be used as guidelines for outcome-driven automated customer service
platforms.Comment: 13 pages, 6 figures, IUI 201
Controller Synthesis for Autonomous Systems Interacting With Human Operators
We propose an approach to synthesize control protocols for autonomous systems that account for uncertainties and imperfections in interactions with human operators. As an illustrative example, we consider a scenario involving road network surveillance by an unmanned aerial vehicle (UAV) that is controlled remotely by a human operator but also has a certain degree of autonomy. Depending on the type (i.e., probabilistic and/or nondeterministic) of knowledge about the uncertainties and imperfections in the operatorautonomy interactions, we use abstractions based on Markov decision processes and augment these models to stochastic two-player games. Our approach enables the synthesis of operator-dependent optimal mission plans for the UAV, highlighting the effects of operator characteristics (e.g., workload, proficiency, and fatigue) on UAV mission performance; it can also provide informative feedback (e.g., Pareto curves showing the trade-offs between multiple mission objectives), potentially assisting the operator in decision-making
Probabilistic Model Checking for Energy Analysis in Software Product Lines
In a software product line (SPL), a collection of software products is
defined by their commonalities in terms of features rather than explicitly
specifying all products one-by-one. Several verification techniques were
adapted to establish temporal properties of SPLs. Symbolic and family-based
model checking have been proven to be successful for tackling the combinatorial
blow-up arising when reasoning about several feature combinations. However,
most formal verification approaches for SPLs presented in the literature focus
on the static SPLs, where the features of a product are fixed and cannot be
changed during runtime. This is in contrast to dynamic SPLs, allowing to adapt
feature combinations of a product dynamically after deployment. The main
contribution of the paper is a compositional modeling framework for dynamic
SPLs, which supports probabilistic and nondeterministic choices and allows for
quantitative analysis. We specify the feature changes during runtime within an
automata-based coordination component, enabling to reason over strategies how
to trigger dynamic feature changes for optimizing various quantitative
objectives, e.g., energy or monetary costs and reliability. For our framework
there is a natural and conceptually simple translation into the input language
of the prominent probabilistic model checker PRISM. This facilitates the
application of PRISM's powerful symbolic engine to the operational behavior of
dynamic SPLs and their family-based analysis against various quantitative
queries. We demonstrate feasibility of our approach by a case study issuing an
energy-aware bonding network device.Comment: 14 pages, 11 figure
PageRank Optimization by Edge Selection
The importance of a node in a directed graph can be measured by its PageRank.
The PageRank of a node is used in a number of application contexts - including
ranking websites - and can be interpreted as the average portion of time spent
at the node by an infinite random walk. We consider the problem of maximizing
the PageRank of a node by selecting some of the edges from a set of edges that
are under our control. By applying results from Markov decision theory, we show
that an optimal solution to this problem can be found in polynomial time. Our
core solution results in a linear programming formulation, but we also provide
an alternative greedy algorithm, a variant of policy iteration, which runs in
polynomial time, as well. Finally, we show that, under the slight modification
for which we are given mutually exclusive pairs of edges, the problem of
PageRank optimization becomes NP-hard.Comment: 30 pages, 3 figure
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