8,554 research outputs found
Buffered Simulation Games for B\"uchi Automata
Simulation relations are an important tool in automata theory because they
provide efficiently computable approximations to language inclusion. In recent
years, extensions of ordinary simulations have been studied, for instance
multi-pebble and multi-letter simulations which yield better approximations and
are still polynomial-time computable.
In this paper we study the limitations of approximating language inclusion in
this way: we introduce a natural extension of multi-letter simulations called
buffered simulations. They are based on a simulation game in which the two
players share a FIFO buffer of unbounded size. We consider two variants of
these buffered games called continuous and look-ahead simulation which differ
in how elements can be removed from the FIFO buffer. We show that look-ahead
simulation, the simpler one, is already PSPACE-hard, i.e. computationally as
hard as language inclusion itself. Continuous simulation is even EXPTIME-hard.
We also provide matching upper bounds for solving these games with infinite
state spaces.Comment: In Proceedings AFL 2014, arXiv:1405.527
A multi-paradigm language for reactive synthesis
This paper proposes a language for describing reactive synthesis problems
that integrates imperative and declarative elements. The semantics is defined
in terms of two-player turn-based infinite games with full information.
Currently, synthesis tools accept linear temporal logic (LTL) as input, but
this description is less structured and does not facilitate the expression of
sequential constraints. This motivates the use of a structured programming
language to specify synthesis problems. Transition systems and guarded commands
serve as imperative constructs, expressed in a syntax based on that of the
modeling language Promela. The syntax allows defining which player controls
data and control flow, and separating a program into assumptions and
guarantees. These notions are necessary for input to game solvers. The
integration of imperative and declarative paradigms allows using the paradigm
that is most appropriate for expressing each requirement. The declarative part
is expressed in the LTL fragment of generalized reactivity(1), which admits
efficient synthesis algorithms, extended with past LTL. The implementation
translates Promela to input for the Slugs synthesizer and is written in Python.
The AMBA AHB bus case study is revisited and synthesized efficiently,
identifying the need to reorder binary decision diagrams during strategy
construction, in order to prevent the exponential blowup observed in previous
work.Comment: In Proceedings SYNT 2015, arXiv:1602.0078
Modeling the Psychology of Consumer and Firm Behavior with Behavioral Economics
Marketing is an applied science that tries to explain and influence how firms and
consumers actually behave in markets. Marketing models are usually applications of
economic theories. These theories are general and produce precise predictions, but they
rely on strong assumptions of rationality of consumers and firms. Theories based on
rationality limits could prove similarly general and precise, while grounding theories in
psychological plausibility and explaining facts which are puzzles for the standard
approach.
Behavioral economics explores the implications of limits of rationality. The goal is to
make economic theories more plausible while maintaining formal power and accurate
prediction of field data. This review focuses selectively on six types of models used in
behavioral economics that can be applied to marketing.
Three of the models generalize consumer preference to allow (1) sensitivity to reference
points (and loss-aversion); (2) social preferences toward outcomes of others; and (3)
preference for instant gratification (quasi-hyperbolic discounting). The three models are
applied to industrial channel bargaining, salesforce compensation, and pricing of virtuous
goods such as gym memberships. The other three models generalize the concept of gametheoretic
equilibrium, allowing decision makers to make mistakes (quantal response
equilibrium), encounter limits on the depth of strategic thinking (cognitive hierarchy),
and equilibrate by learning from feedback (self-tuning EWA). These are applied to
marketing strategy problems involving differentiated products, competitive entry into
large and small markets, and low-price guarantees.
The main goal of this selected review is to encourage marketing researchers of all kinds
to apply these tools to marketing. Understanding the models and applying them is a
technical challenge for marketing modelers, which also requires thoughtful input from
psychologists studying details of consumer behavior. As a result, models like these could
create a common language for modelers who prize formality and psychologists who prize
realism
Thinking about Attention in Games: Backward and Forward Induction
Behavioral economics improves economic analysis by using psychological
regularity to suggest limits on rationality and self-interest (e.g. Camerer and
Loewenstein 2003). Expressing these regularities in formal terms permits productive
theorizing, suggests new experiments, can contribute to psychology,
and can be used to shape economic policies which make normal people
better off
Routing Games with Progressive Filling
Max-min fairness (MMF) is a widely known approach to a fair allocation of
bandwidth to each of the users in a network. This allocation can be computed by
uniformly raising the bandwidths of all users without violating capacity
constraints. We consider an extension of these allocations by raising the
bandwidth with arbitrary and not necessarily uniform time-depending velocities
(allocation rates). These allocations are used in a game-theoretic context for
routing choices, which we formalize in progressive filling games (PFGs).
We present a variety of results for equilibria in PFGs. We show that these
games possess pure Nash and strong equilibria. While computation in general is
NP-hard, there are polynomial-time algorithms for prominent classes of
Max-Min-Fair Games (MMFG), including the case when all users have the same
source-destination pair. We characterize prices of anarchy and stability for
pure Nash and strong equilibria in PFGs and MMFGs when players have different
or the same source-destination pairs. In addition, we show that when a designer
can adjust allocation rates, it is possible to design games with optimal strong
equilibria. Some initial results on polynomial-time algorithms in this
direction are also derived
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