scholarly journals Satisfiability Checking of Strategy Logic with Simple Goals

2021 ◽  
Author(s):  
Magdalena Kacprzak ◽  
Artur Niewiadomski ◽  
Wojciech Penczek
Keyword(s):  
Boolean Model ◽  
New Method ◽  
Process Synthesis ◽  
Sat Problem ◽  
Multi Agent ◽  
Strategy Logic ◽  
Satisfiability Checking

In this paper, we introduce a new method of the satisfiability (SAT) checking for Simple-Goal Strategy Logic (SL[SG]), using symbolic Boolean model encoding and the SAT Modulo Monotonic Theories techniques, which was implemented into the tool SGSAT. To the best of our knowledge, this is the only tool solving the SAT problem for SL[SG]. Its applications include process synthesis, developing controllers as well as automatic planners in multi-agent scenarios.

scholarly journals Representation and Reasoning about Strategic Abilities with ω-Regular Properties

Mathematics ◽  
2021 ◽  
Vol 9 (23) ◽  
pp. 3052
Author(s):  
Liping Xiong ◽  
Sumei Guo
Keyword(s):  
Temporal Logic ◽  
Linear Time ◽  
Dynamic Logic ◽  
Research Area ◽  
Regular Expressions ◽  
Multi Agent Systems ◽  
Practical Applications ◽  
Multi Agent ◽  
Strategy Logic ◽  
Active Research

Specification and verification of coalitional strategic abilities have been an active research area in multi-agent systems, artificial intelligence, and game theory. Recently, many strategic logics, e.g., Strategy Logic (SL) and alternating-time temporal logic (ATL*), have been proposed based on classical temporal logics, e.g., linear-time temporal logic (LTL) and computational tree logic (CTL*), respectively. However, these logics cannot express general ω-regular properties, the need for which are considered compelling from practical applications, especially in industry. To remedy this problem, in this paper, based on linear dynamic logic (LDL), proposed by Moshe Y. Vardi, we propose LDL-based Strategy Logic (LDL-SL). Interpreted on concurrent game structures, LDL-SL extends SL, which contains existential/universal quantification operators about regular expressions. Here we adopt a branching-time version. This logic can express general ω-regular properties and describe more programmed constraints about individual/group strategies. Then we study three types of fragments (i.e., one-goal, ATL-like, star-free) of LDL-SL. Furthermore, we show that prevalent strategic logics based on LTL/CTL*, such as SL/ATL*, are exactly equivalent with those corresponding star-free strategic logics, where only star-free regular expressions are considered. Moreover, results show that reasoning complexity about the model-checking problems for these new logics, including one-goal and ATL-like fragments, is not harder than those of corresponding SL or ATL*.

Proposal of PSwithEFP and its Evaluation in Multi-Agent Reinforcement Learning

2017 ◽  
Vol 21 (5) ◽  
pp. 930-938 ◽  
Author(s):  
Kazuteru Miyazaki ◽  
Koudai Furukawa ◽  
Hiroaki Kobayashi ◽  
◽  
◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Failure Probability ◽  
Action Selection ◽  
New Method ◽  
Selection Strategy ◽  
Multiple Agents ◽  
Learning Problem ◽  
Concurrent Learning ◽  
Multi Agent

When multiple agents learn a task simultaneously in an environment, the learning results often become unstable. This problem is known as the concurrent learning problem and to date, several methods have been proposed to resolve it. In this paper, we propose a new method that incorporates expected failure probability (EFP) into the action selection strategy to give agents a kind of mutual adaptability. The effectiveness of the proposed method is confirmed using Keepaway task.

Multi-Agent Actor Critic for Channel Allocation in Heterogeneous Networks

2020 ◽  
Vol 11 (1) ◽  
pp. 23-41
Author(s):  
Nan Zhao ◽  
Zehua Liu ◽  
Yiqiang Cheng ◽  
Chao Tian
Keyword(s):  
Reinforcement Learning ◽  
Communication Networks ◽  
Heterogeneous Networks ◽  
High Efficiency ◽  
Channel Allocation ◽  
Optimal Solution ◽  
New Method ◽  
Multi Agent ◽  
Optimal Approach ◽  
The Cost

Heterogeneous networks (HetNets) can equalize traffic loads and cut down the cost of deploying cells. Thus, it is regarded to be the significant technique of the next-generation communication networks. Due to the non-convexity nature of the channel allocation problem in HetNets, it is difficult to design an optimal approach for allocating channels. To ensure the user quality of service as well as the long-term total network utility, this article proposes a new method through utilizing multi-agent reinforcement learning. Moreover, for the purpose of solving computational complexity problem caused by the large action space, deep reinforcement learning is put forward to learn optimal policy. A nearly-optimal solution with high efficiency and rapid convergence speed could be obtained by this learning method. Simulation results reveal that this new method has the best performance than other methods.

scholarly journals Automation of microservices creation for qualitative analysis of binary dynamic systems

2019 ◽  
Author(s):  
G.A. Oparin ◽  
V.G. Bogdanova ◽  
A.A. Pashinin
Keyword(s):  
Dynamic System ◽  
Dynamic Systems ◽  
Boolean Model ◽  
Boolean Formula ◽  
Time Interval ◽  
Instrumental System ◽  
Boolean Formulas ◽  
Service Oriented ◽  
Multi Agent ◽  
User Access

The main objective of qualitative research is to analyze the behavior of the trajectories of a dynamic system to verify whether it corresponds to the set of constraints characterizing the property. We use an approach to study binary dynamic systems on a finite time interval based on the author's method of Boolean constraints. Based on this method, the Boolean model of the properties of a binary dynamic system is written in the language of Boolean equations or Boolean formulas with quantifiers. Thus, the verification of various dynamical properties is reduced to solving the problems of Boolean constraints satisfiability or the validity of a quantified Boolean formula using efficient SAT or TQBF solvers. The high computational complexity of these problems requires the development of software and tools for their parallel and distributed solving and ensuring transparent end-user access to highperformance computing environments based on a service-oriented approach. This paper represents the architecture and functionality of a new instrumental system that automates the creation of a distributed application for solving the considered class of problems based on the microservice approach and multi-agent technology.

scholarly journals Verification of Broadcasting Multi-Agent Systems against an Epistemic Strategy Logic

2017 ◽  
Author(s):  
Francesco Belardinelli ◽  
Alessio Lomuscio ◽  
Aniello Murano ◽  
Sasha Rubin
Keyword(s):  
Model Checking ◽  
Secret Sharing ◽  
Imperfect Information ◽  
Multi Agent Systems ◽  
Perfect Recall ◽  
Agent Systems ◽  
Multi Agent ◽  
Strategy Logic

We study a class of synchronous, perfect-recall multi-agent systemswith imperfect information and broadcasting (i.e., fully observableactions). We define an epistemic extension of strategy logic withincomplete information and the assumption of uniform and coherentstrategies. In this setting, we prove that the model checking problem,and thus rational synthesis, is decidable with non-elementarycomplexity. We exemplify the applicability of the framework on arational secret-sharing scenario.

Verification of multi-agent systems with public actions against strategy logic

2020 ◽  
Vol 285 ◽  
pp. 103302 ◽  
Author(s):  
Francesco Belardinelli ◽  
Alessio Lomuscio ◽  
Aniello Murano ◽  
Sasha Rubin
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Strategy Logic

scholarly journals Synthesis of Controllable Nash Equilibria in Quantitative Objective Game

2018 ◽  
Author(s):  
Shaull Almagor ◽  
Orna Kupferman ◽  
Giuseppe Perelli
Keyword(s):  
Social Choice ◽  
Nash Equilibria ◽  
Price Of Anarchy ◽  
Decision Procedures ◽  
Price Of Stability ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
Real Value ◽  
Strategy Logic

In Rational Synthesis, we consider a multi-agent system in which some of the agents are controllable and some are not. All agents have objectives, and the goal is to synthesize strategies for the controllable agents so that their objectives are satisfied, assuming rationality of the uncontrollable agents. Previous work on rational synthesis considers objectives in LTL, namely ones that describe on-going behaviors, and in Objective-LTL, which allows ranking of LTL formulas. In this paper, we extend rational synthesis to LTL[F] -- an extension of LTL by quality operators. The satisfaction value of an LTL[F] formula is a real value in [0,1], where the higher the value is, the higher is the quality in which the computation satisfies the specification. The extension significantly strengthens the framework of rational synthesis and enables a study its game- and social-choice theoretic aspects. In particular, we study the price of stability and price of anarchy of the rational-synthesis game and use them to explain the cooperative and non-cooperative settings of rational synthesis. Our algorithms make use of strategy logic and decision procedures for it. Thus, we are able to handle the richer quantitative setting using existing tools. In particular, we show that the cooperative and non-cooperative versions of quantitative rational synthesis are 2EXPTIME-complete and in 3EXPTIME, respectively -- not harder than the complexity known for their Boolean analogues.

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