Network State Estimation and Prediction for Real-Time Traffic Management

Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS) have the potential to contribute to the solution of the traffic congestion problem. DynaMIT is a real-time system that can be used to generate guidance for travelers. The main principle on which DynaMIT is based is that information should be consistent, and user optimal. Consistency implies that the traffic conditions experienced by the travelers are consistent with the condition assumed in generating the guidance. To generate consistent user optimal information, DynaMIT performs two main functions: state estimation and prediction. A demand simulator and a supply simulator interact to perform these tasks. A case study demonstrates the value of the system.     

Synthesis with rational environments

Synthesis is the automated construction of a system from its specification. The system has to satisfy its specification in all possible environments. The environment often consists of agents that have objectives of their own. Thus, it makes sense to soften the universal quantification on the behavior of the environment and take the objectives of its underlying agents into an account. Fisman et al. introduced rational synthesis: the problem of synthesis in the context of rational agents. The input to the problem consists of temporal logic formulas specifying the objectives of the system and the agents that constitute the environment, and a solution concept (e.g., Nash equilibrium). The output is a profile of strategies, for the system and the agents, such that the objective of the system is satisfied in the computation that is the outcome of the strategies, and the profile is stable according to the solution concept; that is, the agents that constitute the environment have no incentive to deviate from the strategies suggested to them. In this paper we continue to study rational synthesis. First, we suggest an alternative definition to rational synthesis, in which the agents are rational but not cooperative. We call such problem strong rational synthesis. In the strong rational synthesis setting, one cannot assume that the agents that constitute the environment take into account the strategies suggested to them. Accordingly, the output is a strategy for the system only, and the objective of the system has to be satisfied in all the compositions that are the outcome of a stable profile in which the system follows this strategy. We show that strong rational synthesis is 2ExpTime-complete, thus it is not more complex than traditional synthesis or rational synthesis. Second, we study a richer specification formalism, where the objectives of the system and the agents are not Boolean but quantitative. In this setting, the objective of the system and the agents is to maximize their outcome. The quantitative setting significantly extends the scope of rational synthesis, making the game-theoretic approach much more relevant. Finally, we enrich the setting to one that allows coalitions of agents that constitute the system or the environment.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.     

THE IMPORTANCE OF NEUTRAL EXAMPLES FOR LEARNING SENTIMENT

Most research on learning to identify sentiment ignores "neutral" examples, learning only from examples of significant (positive or negative) polarity. We show that it is crucial to use neutral examples in learning polarity for a variety of reasons. Learning from negative and positive examples alone will not permit accurate classification of neutral examples. Moreover, the use of neutral training examples in learning facilitates better distinction between positive and negative examples.     

The specification logic νZ

This paper introduces a wide-spectrum specification logic νZ. The minimal core logic is extended to a more expressive specification logic which includes a schema calculus similar (but not equivalent) to Z, new additional schema operators, and extensions to programming and program development logics.     

Determination of breakdown rates and defect densities in SiO2

Breakdowns in SiO₂ have been classified as defect related, due to wear-out and intrinsic. However, techniques to ascertain defect densities and breakdown rates at defects have not been available, nor has the distinction between wear-out and defect- related or intrinsic breakdowns been clearly demonstrated. A particular problem has been the inability to distinguish defect types, i.e. defects having different breakdown rates. Another source of confusion has been the tacit assumption that breakdown field histograms obtained from ramp breakdown tests are independent of the ramp rate, which cannot be valid for finite breakdown rates. We obtained relationships specifying the statistics of breakdown, including the effect of defects. These actually derive from results describing a Markov death process and depend on the time integrals of breakdown rates in defect-free regions and at defects and on parameters describing the defect distributions. For Poisson distributions of the defect, these parameters are the mean number of defects per device for each defect type. Any breakdown test is described by the same relations since the nature of the test enters only through the time integral of the breakdown rates. If a wear-out mechanism is operative, then the breakdown rates will depend on the time explicitly, i.e. not only via the time dependences of the applied field and temperature. procedures for obtaining defect densities and breakdown rates follow from the derived dependence on these quantities of the expectation value of the fraction of devices broken down. Ramp tests at various ramp rates are advantageous for this purpose. The field dependence of the breakdown rates can be extracted directly from the experimental data and no a priori form for this dependence need be assumed. Experimental results obtained from multiple ramp breakdown tests will be presented. The field dependence of the breakdown rates is found to vary significantly from a simple exponential dependence. Following Klein, the effect of fluctuations on the breakdown rates will be considered qualitatively to rationalize their observed field dependence. No explicit time dependence of the breakdown rates is indicated over the range of field covered by the data, implying the absence of wear-out.     

Learning to Predict Non-Deterministically Generated Strings

In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.     

From object-process analysis to object-process design

The object-process methodology incorporates the system static-structural and dynamic-procedural aspects into a single, unified model. This unification bridges the gap that separates the static, object model from the dynamic, behavior, state, or function-oriented models found in many current object oriented methodologies. In this work we concentrate on the transition from object-process analysis to design within the development of information systems. We use a detailed case study as a running example throughout the paper to demonstrate how the structure-behavior unification, which characterizes object-process analysis, is carried on to object-process design. The case study first applies object-process analysis to perform the analysis stage. The sequence of steps that constitutes the design is then discussed and demonstrated through the case study. The design is divided into two phases: the analysis refinement phase and the implementation-dependent phase. Analysis refinement is concerned with adding details to the analysis results which are beyond the interest of the analysis itself, yet they are not related with a particular implementation. The implementation-dependent phase is concerned with code-level design, which takes place after specific implementation details, such as programming language, data organization, and user interface, have been made during the strategic design.     

A survey on offline scheduling with rejection

In classical deterministic scheduling problems, it is assumed that all jobs have to be processed. However, in many practical cases, mostly in highly loaded make-to-order production systems, accepting all jobs may cause a delay in the completion of orders which in turn may lead to high inventory and tardiness costs. Thus, in such systems, the firm may wish to reject the processing of some jobs by either outsourcing them or rejecting them altogether. The field of scheduling with rejection provides schemes for coordinated sales and production decisions by grouping them into a single model. Since scheduling problems with rejection are very interesting both from a practical and a theoretical point of view, they have received a great deal of attention from researchers over the last decade. The purpose of this survey is to offer a unified framework for offline scheduling with rejection by presenting an up-to-date survey of the results in this field. Moreover, we highlight the close connection between scheduling with rejection and other fields of research such as scheduling with controllable processing times and scheduling with due date assignment, and include some new results which we obtained for open problems.