Rabinizer: Small Deterministic Automata for LTL(F,G)

The paper deals with symbolic approaches to bounded model checking (BMC) for the existential fragment of linear temporal logic extended with the epistemic component (ELTLK), interpreted over interleaved interpreted systems. Two translations of BMC for ELTLK to SAT and to operations on BDDs are presented. The translations have been implemented, tested, and compared with each other as well as with another tool on several benchmarks for MAS. Our experimental results reveal advantages and disadvantages of SAT- versus BDD-based BMC for ELTLK.

Software-controlled bots, also called social bots, are computer programs that act like human users on social media platforms. Recent work on detection of social bots is dominated by machine learning approaches. In this paper we explore bot detection as a model checking problem. We introduce Temporal Network Logic (TNL) which we use to specify social networks where agents can post and follow each other. In this logic we formalize different types of social bot behavior. These are formulas that are satisfied in a model of a network with bots. We provide a simple algorithm to extract a logical model from a real-life social network. We show that we can reduce TNL to a fragment of linear temporal logic with past and use this to establish the computational efficiency of model checking for social bot detection.

Reactive synthesis is an automated procedure to obtain a\ncorrect-by-construction reactive system from a given specification. GR(1) is a\nwell-known fragment of linear temporal logic (LTL) where synthesis is possible\nusing a polynomial symbolic algorithm. We conducted a case study to learn about\nthe challenges that software engineers may face when using GR(1) synthesis for\nthe development of a reactive robotic system. In the case study we developed\ntwo variants of a forklift controller, deployed on a Lego robot. The case study\nemploys LTL specification patterns as an extension of the GR(1) specification\nlanguage, an examination of two specification variants for execution\nscheduling, traceability from the synthesized controller to constraints in the\nspecification, and generated counter strategies to support understanding\nreasons for unrealizability. We present the specifications we developed, our\nobservations, and challenges faced during the case study.\n

We consider the problem of computing the set of initial states of a dynamical system such that there exists a control strategy to ensure that the trajectories satisfy a temporal logic specification with probability 1 (almost-surely). We focus on discrete-time, stochastic linear dynamics and specifications given as formulas of the Generalized Reactivity(1) fragment of Linear Temporal Logic over linear predicates in the states of the system. We propose a solution based on iterative abstraction-refinement, and turn-based 2-player probabilistic games. While the theoretical guarantee of our algorithm after any finite number of iterations is only a partial solution, we show that if our algorithm terminates, then the result is the set of satisfying initial states. Moreover, for any (partial) solution our algorithm synthesizes witness control strategies to ensure almost-sure satisfaction of the temporal logic specification. We demonstrate our approach on an illustrative case study.

Property specifications for workflow modelling

ASQ-IT: Interactive explanations for reinforcement-learning agents

Recent development of logic programming languages based on linear logic suggests a successful direction to extend logic programming to be more expressive and more efficient. The treatment of formulasas-resources gives us not only powerful expressiveness, but also efficient access to a large set of data. However, in linear logic, whole resources are kept in one context, and there is no straight way to represent complex data structures as resources. For example, in order to represent an ordered list and time-dependent data, we need to put additional indices for each resource formula. This paper describes a logic programming language, called TLLP, based on intuitionistic temporal linear logic. This logic, an extension of linear logic with some features from temporal logics, allows the use of the modal operators '?'(next-time) and '?'(always) in addition to the operators used in intuitionistic linear logic. The intuitive meaning of modal operators is as follows: ? B means that B can be used exactly once at the next moment in time; ? B means that B can be used exactly once any time; !B means that B can be used arbitrarily many times (including 0 times) at any time. We first give a proof theoretic formulation of the logic of the TLLP language. We then present a series of resource management systems designed to implement not only interpreters but also compilers based on an extension of the standard WAM model.

This paper proposes an online human-aware behavior planning method to enable Unmanned Aerial Vehicles (UAVs) to dynamically satisfy high-level linear temporal logic (LTL) task descriptions from human collaborators. The proposed method has the potential to be applied to the industrial human–UAV collaboration. The specific process is as follows. Firstly, the global high-level task of the UAV is described using the formal language of LTL, which can usually be issued by human collaborators in natural language. Secondly, the task description is transformed into a deterministic Rabin automaton, and then the state values of the automaton are given by the distance from the accepted states. Thirdly, the Markov decision process is used to construct the probabilistic behavior model of the UAV offline. Based on this model, a finite state automaton in the finite horizon is dynamically constructed online, and the Cartesian product system within the horizon is constructed, in which the expected arrival states within the horizon are set by the minimum state values. Finally, aiming at maximizing the reachability probability of the expected states, the value iterative algorithm is introduced to solve the optimal behavior plan online within the finite horizon. After it, an infinite horizon planning and execution algorithm is formed. Experiments and analysis show that the results of the online behavior planning are consistent with the task logic at the semantic level, indicating the correctness of the proposed method. Moreover, the proposed method can effectively alleviate the state explosion caused by the global probabilistic model checking and improve the efficiency of plan generation.

This article aims to generate all theorems of a given size in the implicational fragment of propositional intuitionistic linear logic. It was presented at the 36th International Conference on Logic Programming (ICLP).

In this paper, We consider an uncertain Markov decision process (MDP) with a control cost and a linear temporal logic (LTL) control specification. We propose a reinforcement learning (RL) based method for design of an optimal control policy by which the controlled MDP satisfies the control specification with probability 1 and minimizes an expected discounted sum of the control costs. First, we construct a deterministic Rabin automaton (DRA) that accepts all and only infinite words satisfying the LTL control specification. Second, we construct a product MDP of the MDP and the DRA to represent a dynamic control policy that satisfies the control specification. Third, we modify the product MDP in order to apply RL to the design of an optimal control policy. The control action of the modified product MDP is a pair of a pattern and an action, where the pattern is a set of actions. Moreover, we introduce a reward that represents both the satisfaction of the control specification and the minimally restrictiveness of the pattern. Finally, we proposed an algorithm for design of an optimal control policy that consists of a sequential decision making of two steps. At the first decision making, we select a pattern that maximizes a discounted sum of the reward. At the second one, we select an action from the pattern selected at the first one such that it minimizes the expected discounted sum of the costs. Moreover, we consider an illustrative example to show that the proposed algorithm can obtain an optimal control policy.

We present a unified translation of linear temporal logic (LTL) formulas into deterministic Rabin automata (DRA), limit-deterministic Büchi automata (LDBA), and nondeterministic Büchi automata (NBA). The translations yield automata of asymptotically optimal size (double or single exponential, respectively). All three translations are derived from one single Master Theorem of purely logical nature. The Master Theorem decomposes the language of a formula into a positive Boolean combination of languages that can be translated into ω-automata by elementary means. In particular, Safra’s, ranking, and breakpoint constructions used in other translations are not needed. We further give evidence that this theoretical clean and compositional approach does not lead to large automata per se and in fact in the case of DRAs yields significantly smaller automata compared to the previously known approach using determinisation of NBAs.

In the mid 1980s, Lichtenstein, Pnueli, and Zuck proved a classical theorem stating that every formula of Past LTL (the extension of Linear Temporal Logic (LTL) with past operators) is equivalent to a formula of the form \(\bigwedge _{i=1}^n {\mathbf {G}}{\mathbf {F}}\varphi _i \vee {\mathbf {F}}{\mathbf {G}}\psi _i\) , where φ i and ψ i contain only past operators. Some years later, Chang, Manna, and Pnueli built on this result to derive a similar normal form for LTL. Both normalization procedures have a non-elementary worst-case blow-up, and follow an involved path from formulas to counter-free automata to star-free regular expressions and back to formulas. We improve on both points. We present direct and purely syntactic normalization procedures for LTL, yielding a normal form very similar to the one by Chang, Manna, and Pnueli, that exhibit only a single exponential blow-up. As an application, we derive a simple algorithm to translate LTL into deterministic Rabin automata. The algorithm normalizes the formula, translates it into a special very weak alternating automaton, and applies a simple determinization procedure, valid only for these special automata.

This paper presents a high level strategy planning framework for the UAV, in which the strategy planning problem under uncertain conditions is abstracted into Markov Decision Processes with uncertain parameters, and the mission requirements are specified using Linear Temporal Logic Language. The objective is to compute a robust satisfying policy to maximize the robustness to the uncertainty while satisfying the desired requirements of system performance or the mission specification. The info-gap decision model is used to describe the uncertain parameters of MDP, i.e., the transition probability, and thus we propose a new model as Info-gap based MDPs (IMDPs). The LTL formula of mission specifications is converted to Deterministic Rabin Automaton (DRA). A product IMDP is constructed by combing the IMDP with DRA in the form of Cartesian product. Based on robust dynamic programming, we propose a robust satisfying policy generation algorithm to solve the product IMDP. An example of UAV high level strategy planning is given to verify our algorithm and the resulting policy can maximize the robustness while satisfying the mission specifications.

1.1 Relationship between Petri net and linear logic Petri nets were first introduced by Petri in his seminal Ph.D. thesis, and both the theory and the applications of his model have flourished in concurrency theory (Reisig & Rozenberg, 1998a; Reisig & Rozenberg, 1998b). The relationships between Petri nets and linear logics have been studied by many researchers (Engberg & Winskel, 1997; Farwer, 1999; Hirai, 2000; Hirai 1999; Ishihara & Hiraish, 2001; Kamide, 2004, Kamide, 2006; Kanovich, 1995; Kanovich 1994; LarcheyWendling & Galmiche, 1998; Larchey-Wendling & Galmiche, 2000; Lilius, 1992; Mart -Oliet & Meseguer, 1991; Okada, 1998; Tanabe, 1997). A category theoretical investigation of such a relationship was given by Mart -Oliet and Meseguer (Mart -Oliet & Meseguer, 1991), purely syntactical approach using Horn linear logic was established by Kanovich (Kanovich, 1995; Kanovich 1994), a naive phase linear logic for a certain class of Petri nets was given by Okada (Okada, 1998), a linear logical view of object Petri nets were studied by Farwer (Farwer, 1999), and various Petri net interpretations of linear logic using quantale models were obtained by Ishihara and Hiraishi (Ishihara & Hiraish, 2001), Engberg and Winskel (Engberg & Winskel, 1997), Larchey-Wendling and Galmiche (Larchey-Wendling & Galmiche, 1998; Larchey-Wendling & Galmiche, 2000), and Lilius (Lilius, 1992). Petri net interpretations using Kripke semantics for various fragments and extensions of intuitionistic linear logic were studied by Kamide (Kamide, 2004; Kamide, 2006c). In (Kamide, 2004), Petri net interpretations of various fragments of a spatio-temporal soft linear logic were discussed. In (Kamide, 2006c), Petri nets with inhibitor arcs, which were first introduced by Kosaraju (Kosaraju, 1973) to show the limitation of the usual Petri nets, were described using Kripke semantics for intuitionistic linear logic with strong negation. The approarches using Kripke semantics can obtain a very simple correspondence between Petri net and linear logic.

A graph-theoretic characterization theorem for multiplicative fragment of non-commutative linear logic