824 research outputs found
MCMAS-SLK: A Model Checker for the Verification of Strategy Logic Specifications
We introduce MCMAS-SLK, a BDD-based model checker for the verification of
systems against specifications expressed in a novel, epistemic variant of
strategy logic. We give syntax and semantics of the specification language and
introduce a labelling algorithm for epistemic and strategy logic modalities. We
provide details of the checker which can also be used for synthesising agents'
strategies so that a specification is satisfied by the system. We evaluate the
efficiency of the implementation by discussing the results obtained for the
dining cryptographers protocol and a variant of the cake-cutting problem
Strategic Abilities of Asynchronous Agents: Semantic Side Effects and How to Tame Them
Recently, we have proposed a framework for verification of agents' abilities
in asynchronous multi-agent systems, together with an algorithm for automated
reduction of models. The semantics was built on the modeling tradition of
distributed systems. As we show here, this can sometimes lead to
counterintuitive interpretation of formulas when reasoning about the outcome of
strategies. First, the semantics disregards finite paths, and thus yields
unnatural evaluation of strategies with deadlocks. Secondly, the semantic
representations do not allow to capture the asymmetry between proactive agents
and the recipients of their choices. We propose how to avoid the problems by a
suitable extension of the representations and change of the execution semantics
for asynchronous MAS. We also prove that the model reduction scheme still works
in the modified framework
Discourses on social software
Can computer scientists contribute to the solution of societal problems? Can logic help to model social interactions? Are there recipes for making groups with diverging preferences arrive at reasonable decisions? Why is common knowledge important for social interaction? Does the rational pursuit of individual interests put the public interest in danger, and if so, why? Discourses on Social Software sheds light on these and similar questions. This book offers the reader an ideal introduction to the exciting new field of social software. It shows in detail the many ways in which the seemingly abstract sciences of logic and computer science can be put to use to analyse and solve contemporary social problems. The unusual format of a series of discussions among a logician, a computer scientist, a philosopher and some researchers from other disciplines encourages the reader to develop his own point of view. The only requirements for reading this book are a nodding familiarity with logic, a curious mind, and a taste for spicy debate.Kunnen de computerwetenschappers bijdragen aan een oplossing van sociale problemen? Kan logica gebruikt worden om sociale interactie te modelleren? Zijn er regels op te stellen om groepen met afwijkende voorkeuren tot redelijke besluiten te laten komen? Discourses on Social Software biedt de lezer een ideale inleiding op (nog nieuwe) gebied van sociale software. Het toont in detail de vele manieren waarin de schijnbaar abstracte wetenschappen van logica en computerwetenschap aan het werk kunnen worden gezet om eigentijdse sociale problemen te analyseren en op te lossen. Door de ongebruikelijke aanpak in dit boek, namelijk door discussies tussen een logicus, een computerwetenschapper, een filosoof en onderzoekers uit andere disciplines, wordt de lezer aangemoedigd zijn eigen standpunt te ontwikkelen. De enige vereisten om dit boek te lezen zijn enige vertrouwdheid met de logica, een nieuwsgierige geest, en liefde voor een pittig debat
Verifying one hundred prisoners and a lightbulb
This is a case-study in knowledge representation and
dynamic epistemic protocol verification. We analyze the `one hundred
prisoners and a lightbulb' puzzle. In this puzzle it is relevant
what the agents (prisoners) {\em know}, how their knowledge {\em
changes} due to {\em observations}, and how they affect the state
of the world by {\em changing facts}, i.e., by their actions. These
actions depend on the history of previous actions and
observations. Part of its interest is that all actions are {\em
local}, i.e.\ not publicly observable, and part of the problem is
therefore how to disseminate local results to other agents, and make
them {\em global}. The various solutions to the puzzle are presented
as protocols (iterated functions from agent's local states, and
histories of actions, to actions
Strategic Abilities of Forgetful Agents in Stochastic Environments
In this paper, we investigate the probabilistic variants of the strategy
logics ATL and ATL* under imperfect information. Specifically, we present novel
decidability and complexity results when the model transitions are stochastic
and agents play uniform strategies. That is, the semantics of the logics are
based on multi-agent, stochastic transition systems with imperfect information,
which combine two sources of uncertainty, namely, the partial observability
agents have on the environment, and the likelihood of transitions to occur from
a system state. Since the model checking problem is undecidable in general in
this setting, we restrict our attention to agents with memoryless (positional)
strategies. The resulting setting captures the situation in which agents have
qualitative uncertainty of the local state and quantitative uncertainty about
the occurrence of future events. We illustrate the usefulness of this setting
with meaningful examples
Comparing approaches for model-checking strategies under imperfect information and fairness constraints
Starting from Alternating-time Temporal Logic, many logics for reasoning about strategies in a system of agents have been proposed. Some of them consider the strategies that agents can play when they have partial information about the state of the system. ATLKirF is such a logic to reason about uniform strategies under unconditional fairness constraints. While this kind of logics has been extensively studied, practical approaches for solving their model- checking problem appeared only recently.
This paper considers three approaches for model checking strategies under partial observability of the agents, applied to ATLKirF . These three approaches have been implemented in PyNuSMV, a Python library based on the state-of- the-art model checker NuSMV. Thanks to the experimental results obtained with this library and thanks to the comparison of the relative performance of the approaches, this paper provides indications and guidelines for the use of these verification techniques, showing that different approaches are needed in different situations
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