1,720,966 research outputs found
Liveness of parameterized timed networks
We consider the model checking problem of infinite state systems given in the form of parameterized discrete timed networks with multiple clocks. We show that this problem is decidable with respect to specifications given by B- or S-automata. Such specifications are very expressive (they strictly subsume ω-regular specifications), and easily express complex liveness and safety properties. Our results are obtained by modeling the passage of time using symmetric broadcast, and by solving the model checking problem of parameterized systems of untimed processes communicating using k-wise rendezvous and symmetric broadcast. Our decidability proof makes use of automata theory, rational linear programming, and geometric reasoning for solving certain reachability questions in vector addition systems; we believe these proof techniques will be useful in solving related problems
Beyond Strong-Cyclic: Doing Your Best in Stochastic Environments
“Strong-cyclic policies” were introduced to formalize trial-and-error strategies and are known to work in Markovian stochastic domains, i.e., they guarantee that the goal is reached with probability 1. We introduce “best-effort” policies for (not necessarily Markovian) stochastic domains. These generalize strong-cyclic policies by taking advantage of stochasticity even if the goal cannot be reached with probability 1. We compare such policies with optimal policies, i.e., policies that maximize the probability that the goal is achieved, and show that optimal policies are best-effort, but that the converse is false in general. With this framework at hand, we revisit the foundational problem of what it means to plan in nondeterministic domains when the nondeterminism has a stochastic nature. We show that one can view a nondeterministic planning domain as a representation of infinitely many stochastic domains with the same support but different probabilities, and that for temporally extended goals expressed in LTL/LTLf a finite-state best-effort policy in one of these domains is best-effort in each of the domains. In particular, this gives an approach for finding such policies that reduces to solving finite-state MDPs with LTL/LTLf goals. All this shows that “best-effort” policies are robust to changes in the probabilities, as long as the support is unchanged
Verification of agent navigation in partially-known environments
This paper establishes a framework based on logic and automata theory in which to model and automatically verify systems of multiple mobile agents moving in environments with partially-known topologies, i.e., ones which are not completely known at design time. Examples include physical agents designed to be used in many spatial environments and not tailored for a specific one, robots in environments not reachable by humans, and software exploring partially-mapped networks. We model spatial environments as graphs whose edges are labelled with directions. We model agents as finite-state machines that move on the graphs by issuing commands of the form “go in direction X”, that can communicate their internal state to other agents, and that can sense agent positions (including current and visited positions). We treat the incomplete information about the spatial environment by studying the decision problem that asks whether a given collection of agents achieve their tasks on all graphs from a class of graphs — this is called the parameterised verification problem. The framework also introduces a new logical language based on Linear Temporal Logic that is tailored for expressing agent navigation tasks in such environments. Although the parameterised verification problem is undecidable, we identify two key dimensions that need to be limited in order to regain decidability, namely, the set of graph-environments and the amount of sensing and communication between agents. In particular, one should limit the families of graphs to exclude grids, and there should be a bound on the number of times an agent senses the position of another agent or communicates its own state to another agent. We prove that dropping either of these assumptions results in undecidability, even for agents with severe restrictions on their abilities (e.g., with very limited sensing abilities and no communication abilities). The importance of this work is that a) it provides a general computational model for mobile multi-agent systems in environments with partially-known topologies, b) it identifies, for the first time, the precise causes of undecidability of these systems and presents minimal restrictions to alleviate this problem, and c) it provides a generic sound and complete procedure for solving the parameterised verification problem over a broad range of spatial-environments and for agents with very powerful sensing and communication abilities
Probabilistic strategy logic
We introduce Probabilistic Strategy Logic, an extension of Strategy Logic for stochastic systems. The logic has probabilistic terms that allow it to express many standard solution concepts, such as Nash equilibria in randomised strategies, as well as constraints on probabilities, such as independence. We study the model-checking problem for agents with perfect- and imperfect-recall. The former is undecidable, while the latter is decidable in space exponential in the system and triple-exponential in the formula. We identify a natural fragment of the logic, in which every temporal operator is immediately preceded by a probabilistic operator, and show that it is decidable in space exponential in the system and the formula, and double-exponential in the nesting depth of the probabilistic terms. Taking a fixed nesting depth, this gives a fragment that still captures many standard solution concepts, and is decidable in exponential space. </p
Stochastic Best-Effort Strategies for Borel Goals
We study reactive systems with Borel goals operating in a possibly non-Markovian stochastic environment. Moreover, the specific environment is not known, only its support is, i.e., at each step one knows which transitions are possible and which are impossible, but the probability distribution amongst the possible transitions is unknown. We consider system strategies that are maximal in the dominance order, i.e., no other strategy achieves the goal with at least the same probability in all environments, and with a higher probability in some environment. We call such strategies "stochastic best-effort". We prove the very general result that stochastic best-effort strategies exist for any Borel goal. We do this by providing local characterizations in terms of a three-valued abstraction of the probability of achieving the goal at a history. The correctness of the characterization is shown using a version of the Lebesgue Density Theorem from geometric measure theory. On the more practical side, we consider goals given in linear temporal logic. We establish the computational complexity of synthesizing a stochastic best-effort strategy, and show that it is not harder than synthesizing an optimal strategy in a domain with fixed known probabilities
Reactive Synthesis of Dominant Strategies
We study the synthesis under environment specifications problem for LTL/LTLf which, in particular, generalizes FOND (strong) planning with these temporal goals. We consider the case where the agent cannot enforce its goal --- for which the argument for using best-effort strategies has been made --- and study the intermediate ground, between enforcing and best-effort strategies, of dominant strategies. Intuitively, such strategies achieve the goal against any environment for which it is achievable.
We show that dominant strategies may exist when enforcing ones do not, while still sharing with the latter many desirable properties such as being interchangeable with each other, and being monotone with respect to tightening of environment specifications. We give necessary and sufficient conditions for the existence of dominant strategies, and show that deciding if they exist is 2EXPTIME-complete --- the same as for enforcing strategies. Finally, we give a uniform, optimal, game-theoretic algorithm for simultaneously solving the three synthesis problems of enforcing, dominant, and best-effort strategies
Parameterized Model-checking of Discrete-Timed Networks and Symmetric-Broadcast Systems
We study the complexity of the model-checking problem for parameterized discrete-timed systems with arbitrarily many anonymous and identical contributors, with and without a distinguished “controller”, and communicating via asynchronous rendezvous. Our work extends the seminal work from German and Sistla on untimed systems by adding discrete-time clocks to processes. For the case without a controller, we show that the systems can be efficiently simulated — and vice versa — by systems of untimed processes that communicate via rendezvous and symmetric broadcast, which we call “RB-systems”. Symmetric broadcast is a novel communication primitive that allows all processes to synchronize at once; however, it does not distinguish between sending and receiving processes. We show that the parameterized model-checking problem for safety specifications is pspace-complete, and for liveness specifications it is decidable in exptime. The latter result is proved using automata theory, rational linear programming, and geometric reasoning for solving certain reachability questions in a new variant of vector addition systems called “vector rendezvous systems”. We believe these proof techniques are of independent interest and will be useful in solving related problems. For the case with a controller, we show that the parameterized model-checking problems for RB-systems and systems with asymmetric broadcast as a primitive are inter-reducible. This allows us to prove that for discrete timed-networks with a controller the parameterized model-checking problem is undecidable for liveness specifications. Our work exploits the intimate connection between parameterized discrete-timed systems and systems of processes communicating via broadcast, providing a rare and surprising decidability result for liveness properties of parameterized timed-systems, as well as extend work from untimed systems to timed systems
Synthesizing strategies under expected and exceptional environment behaviors
We consider an agent that operates with two models of the environment: one that captures expected behaviors and one that captures additional exceptional behaviors. We study the problem of synthesizing agent strategies that enforce a goal against environments operating as expected while also making a best effort against exceptional environment behaviors. We formalize these concepts in the context of linear-temporal logic, and give an algorithm for solving this problem. We also show that there is no trade-off between enforcing the goal under the expected environment specification and making a best-effort for it under the exceptional one
LTLf Synthesis Under Environment Specifications for Reachability and Safety Properties
In this paper, we study LTLf synthesis under environment specifications for arbitrary reachability and safety properties. We consider both kinds of properties for both agent tasks and environment specifications, providing a complete landscape of synthesis algorithms. For each case, we devise a specific algorithm (optimal wrt complexity of the problem) and prove its correctness. The algorithms combine common building blocks in different ways. While some cases are already studied in literature others are studied here for the first time
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