Fully Observable Non-deterministic Planning as Assumption-Based Reactive Synthesis

We contribute to recent efforts in relating two approaches to automatic synthesis, namely, automated planning and discrete reactive synthesis. First, we develop a declarative characterization of the standard “fairness” assumption on environments in non-deterministic planning, and show that strong-cyclic plans are correct solution concepts for fair environments. This complements, and arguably completes, the existing foundational work on non-deterministic planning, which focuses on characterizing (and computing) plans enjoying special “structural” properties, namely loopy but closed policy structures. Second, we provide an encoding suitable for reactive synthesis that avoids the naive exponential state space blowup. To do so, special care has to be taken to specify the fairness assumption on the environment in a succinct manner.Fil: D'ippolito, Nicolás Roque. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigación en Ciencias de la Computación. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigación en Ciencias de la Computación; ArgentinaFil: Rodriguez, Natalia. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Computación; ArgentinaFil: Sardina, Sebastian. RMIT University; Australi

The Planning Spectrum - One, Two, Three, Infinity

Linear Temporal Logic (LTL) is widely used for defining conditions on the execution paths of dynamic systems. In the case of dynamic systems that allow for nondeterministic evolutions, one has to specify, along with an LTL formula f, which are the paths that are required to satisfy the formula. Two extreme cases are the universal interpretation A.f, which requires that the formula be satisfied for all execution paths, and the existential interpretation E.f, which requires that the formula be satisfied for some execution path. When LTL is applied to the definition of goals in planning problems on nondeterministic domains, these two extreme cases are too restrictive. It is often impossible to develop plans that achieve the goal in all the nondeterministic evolutions of a system, and it is too weak to require that the goal is satisfied by some execution. In this paper we explore alternative interpretations of an LTL formula that are between these extreme cases. We define a new language that permits an arbitrary combination of the A and E quantifiers, thus allowing, for instance, to require that each finite execution can be extended to an execution satisfying an LTL formula (AE.f), or that there is some finite execution whose extensions all satisfy an LTL formula (EA.f). We show that only eight of these combinations of path quantifiers are relevant, corresponding to an alternation of the quantifiers of length one (A and E), two (AE and EA), three (AEA and EAE), and infinity ((AE)* and (EA)*). We also present a planning algorithm for the new language that is based on an automata-theoretic approach, and study its complexity

Relentful Strategic Reasoning in 1 Alternating-Time Temporal Logic

Temporal logics are a well investigated formalism for the specification, verification, and synthesis of reactive systems. Within this family, Alternating-Time Temporal Logic (ATL , for short) has been introduced as a useful generalization of classical linear- and branching-time temporal logics, by allowing temporal operators to be indexed by coalitions of agents. Classically, temporal logics are memoryless: once a path in the computation tree is quantified at a given node, the computation that has led to that node is forgotten. Recently, mCTL has been defined as a memoryful variant of CTL , where path quantification is memoryful. In the context of multi-agent planning, memoryful quantification enables agents to “relent” and change their goals and strategies depending on their history. In this paper, we define mATL , a memoryful extension of ATL , in which a formula is satisfied at a certain node of a path by taking into account both the future and the past. We study the expressive power of mATL , its succinctness, as well as related decision problems. We also investigate the relationship between memoryful quantification and past modalities and show their equivalence. We show that both the memoryful and the past extensions come without any computational price; indeed, we prove that both the satisfiability and the model-checking problems are 2EXPTIME-COMPLETE, as they are for AT

Solving Odd-Fair Parity Games

This paper discusses the problem of efficiently solving parity games where player Odd has to obey an additional 'strong transition fairness constraint' on its vertices -- given that a player Odd vertex $v$ is visited infinitely often, a particular subset of the outgoing edges (called live edges) of $v$ has to be taken infinitely often. Such games, which we call 'Odd-fair parity games', naturally arise from abstractions of cyber-physical systems for planning and control. In this paper, we present a new Zielonka-type algorithm for solving Odd-fair parity games. This algorithm not only shares 'the same worst-case time complexity' as Zielonka's algorithm for (normal) parity games but also preserves the algorithmic advantage Zielonka's algorithm possesses over other parity solvers with exponential time complexity. We additionally introduce a formalization of Odd player winning strategies in such games, which were unexplored previous to this work. This formalization serves dual purposes: firstly, it enables us to prove our Zielonka-type algorithm; secondly, it stands as a noteworthy contribution in its own right, augmenting our understanding of additional fairness assumptions in two-player games.Comment: To be published in FSTTCS 202

Cross organisational compatible workflows generation and execution

With the development of internet and electronics, the demand for electronic and online commerce has increased. This has, in turn, increased the demand for business process automation. Workflow has established itself as the technology used for business process automation. Since business organisations have to work in coordination with many other business organisations in order to succeed in business, the workflows of business organisations are expected to collaborate with those of other business organisations. Collaborating organisations can only proceed in business if they have compatible workflows. Therefore, there is a need for cross organisational workflow collaboration. The dynamism and complexity of online and electronic business and high demand from the market leave the workflows prone to frequent changes. If a workflow changes, it has to be re-engineered as well as reconciled with the workflows of the collaborating organisations. To avoid the continuous re-engineering and reconciliation of workflows, and to reuse the existing units of work done, the focus has recently shifted from modeling workflows to automatic workflow generation. Workflows must proceed to runtime execution, otherwise, the effort invested in the build time workflow modeling is wasted. Therefore, workflow management and collaboration systems must support workflow enactment and runtime workflow collaboration. Although substantial research has been done in build-time workflow collaboration, automatic workflow generation, workflow enactment and runtime workflow collaboration, the integration of these highly inter-dependent aspects of workflow has not been considered in the literature. The research work presented in this thesis investigates the integration of these different aspects. The main focus of the research presented in this thesis is the creation of a framework that is able to generate multiple sets of compatible workflows for multiple collaborating organisations, from their OWLS process definitions and high level goals. The proposed framework also supports runtime enactment and runtime collaboration of the generated workflows

Strong Cyclic Planning Revisited

Several realistic non-deterministic planning domains require plans that encode iterative trial-and-error strategies, e.g., `pick up a block until succeed`. In such domains, a certain effect (e.g., action success) might never be guaranteed a priori of execution and, in principle, iterative plans might loop forever. Here, the planner should generate iterative plans whose executions always have a possibility of terminating and, when they do, they are guaranteed to achieve the goal. In this paper, we define the notion of strong cyclic plan, which formalizes in temporal logic the above informal requirements for iterative plans, define a planning algorithm based on model-checking techniques, and prove that the algorithm is guaranteed to return strong cyclic plans when they exist or to terminate with failure when they do not. We show how this approach can be extended to formalize plans that are guaranteed to achieve the goal and do not involve iterations (strong plans) and plans that have a possibility (but are not guaranteed) to achieve the goal (weak plans). The results presented in this paper constitute a formal account for `planning via model checking` in non-deterministic domains, which has never been provided befor