3,339 research outputs found
Verifying multi-threaded software using SMT-based context-bounded model checking
We describe and evaluate three approaches to model check multi-threaded software with shared variables and locks using bounded model checking based on Satisfiability Modulo Theories (SMT) and our modelling of the synchronization primitives of the Pthread library. In the lazy approach, we generate all possible interleavings and call the SMT solver on each of them individually, until we either find a bug, or have systematically explored all interleavings. In the schedule recording approach, we encode all possible interleavings into one single formula and then exploit the high speed of the SMT solvers. In the underapproximation and widening approach, we reduce the state space by abstracting the number of interleavings from the proofs of unsatisfiability generated by the SMT solvers. In all three approaches, we bound the number of context switches allowed among threads in order to reduce the number of interleavings explored. We implemented these approaches in ESBMC, our SMT-based bounded model checker for ANSI-C programs. Our experiments show that ESBMC can analyze larger problems and substantially reduce the verification time compared to state-of-the-art techniques that use iterative context-bounding algorithms or counter-example guided abstraction refinement
Credimus
We believe that economic design and computational complexity---while already
important to each other---should become even more important to each other with
each passing year. But for that to happen, experts in on the one hand such
areas as social choice, economics, and political science and on the other hand
computational complexity will have to better understand each other's
worldviews.
This article, written by two complexity theorists who also work in
computational social choice theory, focuses on one direction of that process by
presenting a brief overview of how most computational complexity theorists view
the world. Although our immediate motivation is to make the lens through which
complexity theorists see the world be better understood by those in the social
sciences, we also feel that even within computer science it is very important
for nontheoreticians to understand how theoreticians think, just as it is
equally important within computer science for theoreticians to understand how
nontheoreticians think
When planning fails: Individual differences and error-related brain activity in problem solving.
The neuronal processes underlying correct and erroneous problem solving were studied in strong and weak problem-solvers using functional magnetic resonance imaging (fMRI). During planning, the right dorsolateral prefrontal cortex was activated, and showed a linear relationship with the participants' performance level. A similar pattern emerged in right inferior parietal regions for all trials, and in anterior cingulate cortex for erroneously solved trials only. In the performance phase, when the pre-planned moves had to be executed by means of an fMRI-compatible computer mouse, the right dorsolateral prefrontal cortex was again activated jointly with right parahippocampal cortex, and displayed a similar positive relationship with the participants' performance level. Incorrectly solved problems elicited stronger bilateral prefrontal and left inferior parietal activations than correctly solved trials. For both individual ability and trial-specific performance, our results thus demonstrate the crucial involvement of right prefrontal cortex in efficient visuospatial planning
Simon's Bounded Rationality. Origins and use in economic theory
The paper aims to show how Simon's notion of bounded rationality should be interpreted in the light of its connection with artificial intelligence. This connection points out that bounded rationality is a highly structured concept, and sheds light on several implications of Simon's general views on rationality. Finally, offering three paradigmatic examples, the artic1e presents the view that recent approaches, which refer to Simon's heterodox theory, only partially accept the teachings of their inspirer, splitting bounded rationality from the context of artificl al intelligence.
An Introduction to Mechanized Reasoning
Mechanized reasoning uses computers to verify proofs and to help discover new
theorems. Computer scientists have applied mechanized reasoning to economic
problems but -- to date -- this work has not yet been properly presented in
economics journals. We introduce mechanized reasoning to economists in three
ways. First, we introduce mechanized reasoning in general, describing both the
techniques and their successful applications. Second, we explain how mechanized
reasoning has been applied to economic problems, concentrating on the two
domains that have attracted the most attention: social choice theory and
auction theory. Finally, we present a detailed example of mechanized reasoning
in practice by means of a proof of Vickrey's familiar theorem on second-price
auctions
- âŠ