English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Probabilistic model checking is a technique for formal automated reasoningabout software or hardware systems that operate in the context of uncertaintyor stochasticity. It builds upon ideas and techniques from a diverse range offields, from logic, automata and graph theory, to optimisation, numericalmethods and control. In recent years, probabilistic model checking has alsobeen extended to integrate ideas from game theory, notably using models such asstochastic games and solution concepts such as equilibria, to formally verifythe interaction of multiple rational agents with distinct objectives. Thisprovides a means to reason flexibly about agents acting in either anadversarial or a collaborative fashion, and opens up opportunities to tacklenew problems within, for example, artificial intelligence, robotics andautonomous systems. In this paper, we summarise some of the advances in thisarea, and highlight applications for which they have already been used. Wediscuss how the strengths of probabilistic model checking apply, or have thepotential to apply, to the multi-agent setting and outline some of the keychallenges required to make further progress in this field.

Multi-Agent Verification and Control with Probabilistic Model Checking