Inductive Synthesis of Cover-Grammars with the Help of Ant Colony Optimization

A cover-grammar of a finite language is a context-free grammar that accepts all words in the language and possibly other words that are longer than any word in the language. In this paper, we describe an efficient algorithm aided by Ant Colony System that, for a given finite language, synthesizes (constructs) a small cover-grammar of the language. We also check its ability to solve a grammatical inference task through the series of experiments

Kernel P Systems Modelling, Testing and Veri cation

A kernel P system (kP system, for short) integrates in a coherent and elegant manner many of the P system features most successfully used for modelling various applications and, consequently, it provides a framework for analyzing these models. In this paper, we illustrate the modeling capabilities of kernel P systems by showing how other classes of P systems can be represented with this formalism and providing a number of kP system models for sorting algorithms. Furthermore, the problem of testing systems modelled as kP systems is also discussed and a test generation method based on automata is proposed. We also demonstrate how formal veri cation can be used to validate that the given models work as desired

Kernel P systems: from modelling to verification and testing

YesA kernel P system integrates in a coherent and elegant manner some of the most successfully used features of the P systems employed in modelling various applications. It also provides a theoretical framework for analysing these applications and a software environment for simulating and verifying them. In this paper, we illustrate the modelling capabilities of kernel P systems by showing how other classes of P systems can be represented with this formalism and providing a number of kernel P system models for a sorting algorithm and a broadcasting problem. We also show how formal verification can be used to validate that the given models work as desired. Finally, a test generation method based on automata is extended to non-deterministic kernel P systems.The work of MG, FI and RL were supported by a grant of the Romanian National Author- ity for Scientific Research, CNCS-UEFISCDI (project number: PN-II-ID-PCE-2011-3-0688); RCU

On Minimizing Cover Automata for Finite Languages in O(n log n) Time

A deterministic finite automaton (DFA) is called a cover automaton (DFCA) for a finite language L over some alphabet # if L = L(A) # #l , with l being the length of some longest word in L

Motion planning and control: a formal methods approach

Control of complex systems satisfying rich temporal specification has become an increasingly important research area in fields such as robotics, control, automotive, and manufacturing. Popular specification languages include temporal logics, such as Linear Temporal Logic (LTL) and Computational Tree Logic (CTL), which extend propositional logic to capture the temporal sequencing of system properties. The focus of this dissertation is on the control of high-dimensional systems and on timed specifications that impose explicit time bounds on the satisfaction of tasks. This work proposes and evaluates methods and algorithms for synthesizing provably correct control policies that deal with the scalability problems. Ideas and tools from formal verification, graph theory, and incremental computing are used to synthesize satisfying control strategies. Finite abstractions of the systems are generated, and then composed with automata encoding the specifications. The first part of this dissertation introduces a sampling-based motion planning algorithm that combines long-term temporal logic goals with short-term reactive requirements. The specification has two parts: (1) a global specification given as an LTL formula over a set of static service requests that occur at the regions of a known environment, and (2) a local specification that requires servicing a set of dynamic requests that can be sensed locally during the execution. The proposed computational framework consists of two main ingredients: (a) an off-line sampling-based algorithm for the construction of a global transition system that contains a path satisfying the LTL formula, and (b) an on-line sampling-based algorithm to generate paths that service the local requests, while making sure that the satisfaction of the global specification is not affected. The second part of the dissertation focuses on stochastic systems with temporal and uncertainty constraints. A specification language called Gaussian Distribution Temporal Logic is introduced as an extension of Boolean logic that incorporates temporal evolution and noise mitigation directly into the task specifications. A sampling-based algorithm to synthesize control policies is presented that generates a transition system in the belief space and uses local feedback controllers to break the curse of history associated with belief space planning. Switching control policies are then computed using a product Markov Decision Process between the transition system and the Rabin automaton encoding the specification.The approach is evaluated in experiments using a camera network and ground robot. The third part of this dissertation focuses on control of multi-vehicle systems with timed specifications and charging constraints. A rich expressivity language called Time Window Temporal Logic (TWTL) that describes time bounded specifications is introduced. The temporal relaxation of TWTL formulae with respect to the deadlines of tasks is also discussed. The key ingredient of the solution is an algorithm to translate a TWTL formula to an annotated finite state automaton that encodes all possible temporal relaxations of the given formula. The annotated automata are composed with transition systems encoding the motion of all vehicles, and with charging models to produce control strategies for all vehicles such that the overall system satisfies the mission specification. The methods are evaluated in simulation and experimental trials with quadrotors and charging stations