46 research outputs found
Multi-Player Games with LDL Goals over Finite Traces
Linear Dynamic Logic on finite traces LDLf is a powerful logic for reasoning
about the behaviour of concurrent and multi-agent systems.
In this paper, we investigate techniques for both the characterisation and
verification of equilibria in multi-player games with goals/objectives
expressed using logics based on LDLf. This study builds upon a generalisation
of Boolean games, a logic-based game model of multi-agent systems where players
have goals succinctly represented in a logical way.
Because LDLf goals are considered, in the settings we study -- Reactive
Modules games and iterated Boolean games with goals over finite traces --
players' goals can be defined to be regular properties while achieved in a
finite, but arbitrarily large, trace.
In particular, using alternating automata, the paper investigates
automata-theoretic approaches to the characterisation and verification of (pure
strategy Nash) equilibria, shows that the set of Nash equilibria in
multi-player games with LDLf objectives is regular, and provides complexity
results for the associated automata constructions
Multi-player games with LDL goals over finite traces
Linear Dynamic Logic on finite traces (LDLF) is a powerful logic for reasoning about the behaviour of concurrent and multi-agent systems. In this paper, we investigate techniques for both the characterisation and verification of equilibria in multi-player games with goals/objectives expressed using logics based on LDLF. This study builds upon a generalisation of Boolean games, a logic-based game model of multi-agent systems where players have goals succinctly represented in a logical way. Because LDLF goals are considered, in the settings we study—Reactive Modules games and iterated Boolean games with goals over finite traces—players' goals can be defined to be regular properties while achieved in a finite, but arbitrarily large, trace. In particular, using alternating automata, the paper investigates automata-theoretic approaches to the characterisation and verification of (pure strategy Nash) equilibria, shows that the set of Nash equilibria in multi-player games with LDLF objectives is regular, and provides complexity results for the associated automata constructions
LTLf Synthesis with Fairness and Stability Assumptions
In synthesis, assumptions are constraints on the environment that rule out
certain environment behaviors. A key observation here is that even if we
consider systems with LTLf goals on finite traces, environment assumptions need
to be expressed over infinite traces, since accomplishing the agent goals may
require an unbounded number of environment action. To solve synthesis with
respect to finite-trace LTLf goals under infinite-trace assumptions, we could
reduce the problem to LTL synthesis. Unfortunately, while synthesis in LTLf and
in LTL have the same worst-case complexity (both 2EXPTIME-complete), the
algorithms available for LTL synthesis are much more difficult in practice than
those for LTLf synthesis. In this work we show that in interesting cases we can
avoid such a detour to LTL synthesis and keep the simplicity of LTLf synthesis.
Specifically, we develop a BDD-based fixpoint-based technique for handling
basic forms of fairness and of stability assumptions. We show, empirically,
that this technique performs much better than standard LTL synthesis
Enforcing equilibria in multi-agent systems
We introduce and investigate Normative Synthesis: a new class of problems for the equilibrium verification that counters the absence of equilibria by purposely constraining multi-agent systems. We show that norms are powerful enough to ensure a positive answer to every instance of the equilibrium verification problem. Subsequently, we focus on two optimization versions, that aim at providing a solution in compliance with implementation costs. We show that the complexities of our procedures range between 2exptime and 3exptime, thus that the problems are no harder than the corresponding equilibrium verification ones
Two-Stage Technique for LTLf Synthesis Under LTL Assumptions
In synthesis, assumption are constraints on the environments that rule out certain environment behaviors. A key observation is that even if we consider system with LTLf goals on finite traces, assumptions need to be expressed considering infinite traces, using LTL on infinite traces, since the decision to stop the trace is controlled by the agent. To solve synthesis of LTLf goals under LTL assumptions, we could reduce the problem to LTL synthesis. Unfortunately, while synthesis in LTLf and in LTL have the same worst-case complexity (both are 2EXPTIME-complete), the algorithms available for LTL synthesis are much harder in practice than those for LTLf synthesis. Recently, it has been shown that in basic forms of fairness and stability assumptions we can avoid such a detour to LTL and keep the simplicity of LTLf synthesis. In this paper, we generalize these results and show how to effectively handle any kind of LTL assumptions. Specifically, we devise a two-stage technique for solving LTLf under general LTL assumptions and show empirically that this technique performs much better than standard LTL synthesis
Natural Strategic Ability
International audienc
Current and Future Challenges in Knowledge Representation and Reasoning
Knowledge Representation and Reasoning is a central, longstanding, and active
area of Artificial Intelligence. Over the years it has evolved significantly;
more recently it has been challenged and complemented by research in areas such
as machine learning and reasoning under uncertainty. In July 2022 a Dagstuhl
Perspectives workshop was held on Knowledge Representation and Reasoning. The
goal of the workshop was to describe the state of the art in the field,
including its relation with other areas, its shortcomings and strengths,
together with recommendations for future progress. We developed this manifesto
based on the presentations, panels, working groups, and discussions that took
place at the Dagstuhl Workshop. It is a declaration of our views on Knowledge
Representation: its origins, goals, milestones, and current foci; its relation
to other disciplines, especially to Artificial Intelligence; and on its
challenges, along with key priorities for the next decade
Computer Aided Verification
This open access two-volume set LNCS 10980 and 10981 constitutes the refereed proceedings of the 30th International Conference on Computer Aided Verification, CAV 2018, held in Oxford, UK, in July 2018. The 52 full and 13 tool papers presented together with 3 invited papers and 2 tutorials were carefully reviewed and selected from 215 submissions. The papers cover a wide range of topics and techniques, from algorithmic and logical foundations of verification to practical applications in distributed, networked, cyber-physical, and autonomous systems. They are organized in topical sections on model checking, program analysis using polyhedra, synthesis, learning, runtime verification, hybrid and timed systems, tools, probabilistic systems, static analysis, theory and security, SAT, SMT and decisions procedures, concurrency, and CPS, hardware, industrial applications
Computer Aided Verification
This open access two-volume set LNCS 10980 and 10981 constitutes the refereed proceedings of the 30th International Conference on Computer Aided Verification, CAV 2018, held in Oxford, UK, in July 2018. The 52 full and 13 tool papers presented together with 3 invited papers and 2 tutorials were carefully reviewed and selected from 215 submissions. The papers cover a wide range of topics and techniques, from algorithmic and logical foundations of verification to practical applications in distributed, networked, cyber-physical, and autonomous systems. They are organized in topical sections on model checking, program analysis using polyhedra, synthesis, learning, runtime verification, hybrid and timed systems, tools, probabilistic systems, static analysis, theory and security, SAT, SMT and decisions procedures, concurrency, and CPS, hardware, industrial applications
Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)
http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"