Nondeterministic Algorithm Research Articles

Challenges in Autonomous Vehicle Testing and Validation

Software testing is all too often simply a bug hunt rather than a wellconsidered exercise in ensuring quality. A more methodical approach than a simple cycle of system-level test-fail-patch-test will be required to deploy safe autonomous vehicles at scale. The ISO 26262 development V process sets up a framework that ties each type of testing to a corresponding design or requirement document, but presents challenges when adapted to deal with the sorts of novel testing problems that face autonomous vehicles. This paper identifies five major challenge areas in testing according to the V model for autonomous vehicles: driver out of the loop, complex requirements, non-deterministic algorithms, inductive learning algorithms, and failoperational systems. General solution approaches that seem promising across these different challenge areas include: phased deployment using successively relaxed operational scenarios, use of a monitor/actuator pair architecture to separate the most complex autonomy functions from simpler safety functions, and fault injection as a way to perform more efficient edge case testing. While significant challenges remain in safety-certifying the type of algorithms that provide high-level autonomy themselves, it seems within reach to instead architect the system and its accompanying design process to be able to employ existing software safety approaches.

Exponential examples of solving parity games

This paper is devoted to solving certain problems on the computational complexity of deciding the winner in cyclic games. The main result is the proof of the fact that the nondeterministic potential transformation algorithm designed for solving parity games is exponential in terms of computation time.

A Rigorous and Efficient Method To Reweight Very Large Conformational Ensembles Using Average Experimental Data and To Determine Their Relative Information Content.

Flexible polypeptides such as unfolded proteins may access an astronomical number of conformations. The most advanced simulations of such states usually comprise tens of thousands of individual structures. In principle, a comparison of parameters predicted from such ensembles to experimental data provides a measure of their quality. In practice, analyses that go beyond the comparison of unbiased average data have been impossible to carry out on the entirety of such very large ensembles and have, therefore, been restricted to much smaller subensembles and/or nondeterministic algorithms. Here, we show that such very large ensembles, on the order of 10(4) to 10(5) conformations, can be analyzed in full by a maximum entropy fit to experimental average data. Maximizing the entropy of the population weights of individual conformations under experimental χ(2) constraints is a convex optimization problem, which can be solved in a very efficient and robust manner to a unique global solution even for very large ensembles. Since the population weights can be determined reliably, the reweighted full ensemble presents the best model of the combined information from simulation and experiment. Furthermore, since the reduction of entropy due to the experimental constraints is well-defined, its value provides a robust measure of the information content of the experimental data relative to the simulated ensemble and an indication for the density of the sampling of conformational space. The method is applied to the reweighting of a 35,000 frame molecular dynamics trajectory of the nonapeptide EGAAWAASS by extensive NMR (3)J coupling and RDC data. The analysis shows that RDCs provide significantly more information than (3)J couplings and that a discontinuity in the RDC pattern at the central tryptophan is caused by a cluster of helical conformations. Reweighting factors are moderate and consistent with errors in MD force fields of less than 3kT. The required reweighting is larger for an ensemble derived from a statistical coil model, consistent with its coarser nature. We call the method COPER, for convex optimization for ensemble reweighting. Similar advantages of large-scale efficiency and robustness can be obtained for other ensemble analysis methods with convex targets and constraints, such as constrained χ(2) minimization and the maximum occurrence method.

Non-deterministic K-anonymity Algorithm Based Untrusted Third Party for Location Privacy Protection in LBS

Non-deterministic K-anonymity Algorithm Based Untrusted Third Party for Location Privacy Protection in LBS

Electromagnetic and thermal parameter identification method for best prediction of temperature distribution on transformer tank covers

Purpose – The purpose of this paper is to describe a parameter identification method based on multiobjective (MO) deterministic and non-deterministic optimization algorithms to compute the temperature distribution on transformer tank covers. Design/methodology/approach – The strategy for implementing the parameter identification process consists of three main steps. The first step is to define the most appropriate objective function and the identification problem is solved for the chosen parameters using single-objective (SO) optimization algorithms. Then sensitivity to measurement error of the computational model is assessed and finally it is included as an additional objective function, making the identification problem a MO one. Findings – Computations with identified/optimal parameters yield accurate results for a wide range of current values and different conductor arrangements. From the numerical solution of the temperature field, decisions on dimensions and materials can be taken to avoid overheating on transformer covers. Research limitations/implications – The accuracy of the model depends on its parameters, such as heat exchange coefficients and material properties, which are difficult to determine from formulae or from the literature. Thus the goal of the presented technique is to achieve the best possible agreement between measured and numerically calculated temperature values. Originality/value – Differing from previous works found in the literature, sensitivity to measurement error is considered in the parameter identification technique as an additional objective function. Thus, solutions less sensitive to measurement errors at the expenses of a degradation in accuracy are identified by means of MO optimization algorithms.

Nondeterministic Algorithm for Breaking Diffie-Hellman Key Exchange using Self-Assembly of DNA Tiles

The computation based on DNA tile self-assembly has been demonstrated to be scalable, which is consider as a promising technique for computation. In this work, I first show how the tile self-assembly process can be used for computing the modular multiplication by mainly constructing three small systems including addition system, subtraction system and comparing system which can also be parallely implemented the discrete logarithm problem in the finite field GF(p). Then the nondeterministic algorithm is successfully performed to break Diffie-Hellman key exchange with the computation time complexity of Θ(p), and the probability of finding the successful solutions among many parallel executions is proved to be arbitrarily close to 1.

Evaluating Case-Base Maintenance algorithms

The success of a Case-Based Reasoning (CBR) system closely depends on its knowledge-base, named the case-base. The life cycle of CBR systems usually implies updating the case-base with new cases. However, it also implies removing useless cases for reasons of efficiency. This process is known as Case-Base Maintenance (CBM) and, in recent decades, great efforts have been made to automatise this process using different kind of algorithms (deterministic and non-deterministic). Indeed, CBR system designers find it difficult to choose from the wealth of algorithms available to maintain the case-base. Despite the importance of such a key decision, little attention has been paid to evaluating these algorithms. Although classical validation methods have been used, such as Cross-Validation and Hold-Out, they are not always valid for non-deterministic algorithms. In this work, we analyse this problem from a methodological point of view, providing an exhaustive review of these evaluation methods supported by experimentation. We also propose a specific methodology for evaluating Case-Base Maintenance algorithms (the αβ evaluation). Experiment results show that this method is the most suitable for evaluating most of the algorithms and datasets studied.

A Hybrid Iterated Greedy Algorithm for No-Wait Flowshop with Sequence Dependent Setup Times to Minimize Makespan

In this paper, the widespread no-wait flowshop in industries is considered with sequence dependent setup times to minimize makespan. A hybrid iterated greedy framework is constructed. A destruction-reconstruction procedure and a composite local search are introduced to improve the initial solution, respectively. To enhance the diversification of the proposal, a solution acceptance criterion is adopted to accept a worse solution with a probability. An efficient hybrid iterated greedy algorithm is investigated for the considered problem. The proposal is compared with the existing best deterministic heuristics and non-deterministic algorithm on Taillards benchmark instances. Experimental results show that the proposal gets best performance against the deterministic heuristics. The proposed algorithm outperforms the non-deterministic one on most instances with the same computation-time.

Multi-Path QoS Routing Algorithm Based on Disjoint Nodes for Mobile Ad Hoc Networks

. To meet the needs of voice, video and other large multimedia data transmission services, a new multi-path routing protocol, which is named MP-QAODV, with QoS guarantees for MANET was proposed. The Routing method based on disjoint nodes and backup multiple paths was used in the protocol. Through introducing two weights constraints based on single-source and single-path network model, a non-deterministic optimal constraints algorithm was proposed. After introducing and instantiating the path stability factor and the path length factor, mathematical model of their relationship was built. The mathematical model was used to improve AODV protocol and the improved protocol has QoS guarantee. Simulation results showed that MP-QAODV is better than AODV, AOMDV in the aspects such as average end to end delay, packet delivery ratio and route control overhead. The experiment demonstrated the effectiveness of MP-QAODV protocol.

Оптимизация моделирования белковых взаимодействий на многопроцессорных системах с предоставлением доступа к алгоритму через веб-интерфейс

In this work were introduced parallel versions based on OpenMP and MPI technologies of sequential program for modeling immobilized protein interactions. Both versions have shown good scalability and better time indices to compare with the sequential version when running on single processor. Need to mention that modeling of immobilized protein interactions for some compounds have taken more than twenty hours of computations on several hundreds of processors, that is why for such modeling tasks with the great quantity of positions availability of nondeterministic algorithms, providing biologically correct result in reasonable time, seems to be rather important. Selection of stochastic algorithms has proved its value: both Monte-Carlo and simulated bee colony algorithms had found conformation corresponding minimal energy state. Supplying of access to the algorithm via web-interface measures up modern specifications of remote computations and allows the wide circle of specialists use computational power of Moscow State University and, taking into account extending the sphere of application tasks of molecular simulation, the presence of open web-interface providing remote access to the computational clusters is quite an important task.

Global Transformer Design Optimization Using Deterministic and Nondeterministic Algorithms

This paper compares the application of two deterministic and three nondeterministic optimization algorithms to global transformer design optimization (TDO). Two deterministic optimization algorithms (mixed-integer nonlinear programming and heuristic algorithm) are compared to three nondeterministic approaches (harmony search, differential evolution, and genetic algorithm). All these algorithms are integrated in design optimization software applied and verified in the manufacturing industry. The comparison yields significant conclusions on the efficiency of the algorithms and the selection of the most suitable one for the TDO problem.

MPGAfold in dengue secondary structure prediction.

This chapter presents the computational prediction of the secondary structures within the 5' and 3' untranslated regions of the dengue virus serotype 2 (DENV2), with the focus on the conformational prediction of the two dumbbell-like structures, 5' DB and 3' DB, found in the core region of the 3' untranslated region of DENV2. For secondary structure prediction purposes we used a 719 nt-long subgenomic RNA construct from DENV2, which we refer to as the minigenome. The construct combines the 5'-most 226 nt from the 5' UTR and a fragment of the capsid coding region with the last 42 nt from the non-structural protein NS5 coding region and the 451 nt of the 3' UTR. This minigenome has been shown to contain the elements needed for translation, as well as negative strand RNA synthesis. We present the Massively Parallel Genetic Algorithm MPGAfold, a non-deterministic algorithm, that was used to predict the secondary structures of the DENV2 719 nt long minigenome construct, as well as our computational workbench called StructureLab that was used to interactively explore the solution spaces produced by MPGAfold. The MPGAfold algorithm is first introduced at the conceptual level. Then specific parameters guiding its performance are discussed and illustrated with a representative selection of the results from the study. Plots of the solution spaces generated by MPGAfold illustrate the algorithm, while selected secondary structures focus on variable formation of the dumbbell structures and other identified structural motifs. They also serve as illustrations of some of the capabilities of the StructureLab workbench. Results of the computational structure determination calculations are discussed and compared to the experimental data.

On Fast Heuristic Non-deterministic Algorithms and Short Heuristic Proofs

In this paper we study heuristic proof systems and heuristic non-deterministic algorithms. We give an example of a language Y and a polynomial-time samplable distribution D such that the distributional problem Y, D belongs to the complexity class HeurNP but Y ∉ NP if NP ≠ coNP, and Y, D ∉ HeurBPP if NP,PSamp $\nsubseteq$ HeurBPP. For a language L and a polynomial q we define the language padqL composed of pairs x, r where x is an element of L and r is an arbitrary binary string of length at least q|x|. If $D = \{D_n\}^\infty_{n=1}$ is an ensemble of distributions on strings, let D × Uq be a distribution on pairs x, r, where x is distributed according to Dn and r is uniformly distributed on strings of length qn. We show that for every language L in AM there is a polynomial q such that for every distribution D concentrated on the complement of L the distributional problem padqL, D × Uq has a polynomially bounded heuristic proof system. Since graph non-isomorphism GNI is in AM, the above result is applicable to GNI.

A General Vertex Partition Refinement Algorithm for Graph Isomorphism

A general depth-first backtracking algorithm for graph isomorphism with the vertex partition and refinement technique is presented in this paper. The time complexity of this nondeterministic polynomial algorithm is O(nα+3) where nα is the number of backtracking points and (h-1)/2α (h+1)/2 for h=logn in the worst cases. The tests on many types of graphs validated the efficiency of this algorithm for graph isomorphism.

Automated B – H curve identification algorithm combining field simulation with optimisation methods and exploiting parallel computation

The study proposes an automated procedure for linking an identification algorithm implemented in a general-purpose environment (MatLab) with a commercial finite-element code for magnetic field analysis (VF-Opera). The method is used to identify the B–H curves of anisotropic magnetic laminations in the direction normal to the sheet surface with the aid of a multiprocessor computer to benefit from parallel computing. The proposed approach, based on a non-deterministic algorithm, makes it possible to determine the entire B–H curve and is therefore an advancement on the commonly used assumption of constant permeability.

Emergent command and control architecture for dynamic agent communities

Dynamic multi-agent systems require some accountability mechanism to ensure goal distribution and completion. Accountability can be maintained through proper delineation of power. An organisation is well delineated when each member has an unambiguous power relationship with its peers. Since responsibility and authority follow fully de-conflicted patterns, a delineated organisation is well suited for solving problems. This paper describes a non-deterministic agent level algorithm that emergently simulates various organisational structures and maintains a well-delineated power structure. The appropriateness of this algorithm is demonstrated in a highly dynamic, poor communication network system. A metric is provided which quantifies the appropriateness of the emerging organisational structures. A structure is considered appropriate if an unambiguous chain of accountability exists leading to the human overseer of the system.

Safe nondeterminism in a deterministic-by-default parallel language

A number of deterministic parallel programming models with strong safety guarantees are emerging, but similar support for nondeterministic algorithms, such as branch and bound search, remains an open question. We present a language together with a type and effect system that supports nondeterministic computations with a deterministic-by-default guarantee: nondeterminism must be explicitly requested via special parallel constructs (marked nd), and any deterministic construct that does not execute any nd construct has deterministic input-output behavior. Moreover, deterministic parallel constructs are always equivalent to a sequential composition of their constituent tasks, even if they enclose, or are enclosed by, nd constructs. Finally, in the execution of nd constructs, interference may occur only between pairs of accesses guarded by atomic statements, so there are no data races, either between atomic statements and unguarded accesses (strong isolation) or between pairs of unguarded accesses (stronger than strong isolation alone). We enforce the guarantees at compile time with modular checking using novel extensions to a previously described effect system. Our effect system extensions also enable the compiler to remove unnecessary transactional synchronization. We provide a static semantics, dynamic semantics, and a complete proof of soundness for the language, both with and without the barrier removal feature. An experimental evaluation shows that our language can achieve good scalability for realistic parallel algorithms, and that the barrier removal techniques provide significant performance gains.

Integer Factorization of Semi-Primes Based on Analysis of a Sequence of Modular Elliptic Equations

In this paper is demonstrated a method for reduction of integer factorization problem to an analysis of a sequence of modular elliptic equations. As a result, the paper provides a non-deterministic algorithm that computes a factor of a semi-prime integer n=pq, where prime factors p and q are unknown. The proposed algorithm is based on counting points on a sequence of at least four elliptic curves y2=x(x2+b2)(modn) , where b is a control parameter. Although in the worst case, for some n the number of required values of parameter b that must be considered (the number of basic steps of the algorithm) substantially exceeds four, hundreds of computer experiments indicate that the average number of the basic steps does not exceed six. These experiments also confirm all important facts discussed in this paper.

An improved time-space lower bound for tautologies

We show that for all reals c and d such that c 2 d<4 there exists a positive real e such that tautologies of length n cannot be decided by both a nondeterministic algorithm that runs in time n c , and a nondeterministic algorithm that runs in time n d and space n e . In particular, for every $d<\sqrt[3]{4}$ there exists a positive e such that tautologies cannot be decided by a nondeterministic algorithm that runs in time n d and space n e .

Computational Complexity of Liveness Problem of Normal Petri Net

Petri net is a powerful modeling tool for concurrent systems. Liveness, which is a problem to verify there exists no local deadlock, is one of the most important properties of Petri net to analyze. Computational complexity of liveness of a general Petri net is deterministic exponential space. Liveness is studied for subclasses of Petri nets to obtain necessary and sufficient conditions that need less computational cost. These are mainly done using a subset of places called siphons. CS-property, which denotes that every siphon has token(s) in every reachable marking, in one of key properties in liveness analysis. On the other hand, normal Petri net is a subclass of Petri net whose reachability set can be effectively calculated. This paper studies computational complexity of liveness problem of normal Petri nets. First, it is shown that liveness of a normal Petri net is equivalent to cs-property. Then we show this problem is co-NP complete by deriving a nondeterministic algorithm for non-liveness which is similar to the algorithm for liveness suggested by Howell et al. Lastly, we study structural feature of bounded Petri net where liveness and cs-property are equivalent. From this consideration, liveness problem of bounded normal Petri net is shown to be deterministic polynomial time complexity.