18,299 research outputs found
Decidable Models of Recursive Asynchronous Concurrency
Asynchronously communicating pushdown systems (ACPS) that satisfy the
empty-stack constraint (a pushdown process may receive only when its stack is
empty) are a popular decidable model for recursive programs with asynchronous
atomic procedure calls. We study a relaxation of the empty-stack constraint for
ACPS that permits concurrency and communication actions at any stack height,
called the shaped stack constraint, thus enabling a larger class of concurrent
programs to be modelled. We establish a close connection between ACPS with
shaped stacks and a novel extension of Petri nets: Nets with Nested Coloured
Tokens (NNCTs). Tokens in NNCTs are of two types: simple and complex. Complex
tokens carry an arbitrary number of coloured tokens. The rules of NNCT can
synchronise complex and simple tokens, inject coloured tokens into a complex
token, and eject all tokens of a specified set of colours to predefined places.
We show that the coverability problem for NNCTs is Tower-complete. To our
knowledge, NNCT is the first extension of Petri nets, in the class of nets with
an infinite set of token types, that has primitive recursive coverability. This
result implies Tower-completeness of coverability for ACPS with shaped stacks
Bayesian Inference of Social Norms as Shared Constraints on Behavior
People act upon their desires, but often, also act in adherence to implicit
social norms. How do people infer these unstated social norms from others'
behavior, especially in novel social contexts? We propose that laypeople have
intuitive theories of social norms as behavioral constraints shared across
different agents in the same social context. We formalize inference of norms
using a Bayesian Theory of Mind approach, and show that this computational
approach provides excellent predictions of how people infer norms in two
scenarios. Our results suggest that people separate the influence of norms and
individual desires on others' actions, and have implications for modelling
generalizations of hidden causes of behavior.Comment: 7 pages, 5 figures, to appear in CogSci 2019, code available at
https://github.com/ztangent/norms-cogsci1
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