Building and Refining Abstract Planning Cases by Change of Representation Language

ion is one of the most promising approaches to improve the performance of problem solvers. In several domains abstraction by dropping sentences of a domain description -- as used in most hierarchical planners -- has proven useful. In this paper we present examples which illustrate significant drawbacks of abstraction by dropping sentences. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract. However, to achieve a powerful change of the representation language, the abstract language itself as well as rules which describe admissible ways of abstracting states must be provided in the domain model. This new abstraction approach is the core of Paris (Plan Abstraction and Refinement in an Integrated System), a system in which abstract planning cases are automatically learned from given concrete cases. An empirical study in the domain of process planning in mechanical engineering shows significant advantages of the proposed reasoning from abstract cases over classical hierarchical planning.Comment: See http://www.jair.org/ for an online appendix and other files accompanying this articl

A Markovian approach to the mathematical control of NPD projects

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Scaling Robot Motion Planning to Multi-core Processors and the Cloud

Imagine a world in which robots safely interoperate with humans, gracefully and efficiently accomplishing everyday tasks. The robot's motions for these tasks, constrained by the design of the robot and task at hand, must avoid collisions with obstacles. Unfortunately, planning a constrained obstacle-free motion for a robot is computationally complex---often resulting in slow computation of inefficient motions. The methods in this dissertation speed up this motion plan computation with new algorithms and data structures that leverage readily available parallel processing, whether that processing power is on the robot or in the cloud, enabling robots to operate safer, more gracefully, and with improved efficiency. The contributions of this dissertation that enable faster motion planning are novel parallel lock-free algorithms, fast and concurrent nearest neighbor searching data structures, cache-aware operation, and split robot-cloud computation. Parallel lock-free algorithms avoid contention over shared data structures, resulting in empirical speedup proportional to the number of CPU cores working on the problem. Fast nearest neighbor data structures speed up searching in SO(3) and SE(3) metric spaces, which are needed for rigid body motion planning. Concurrent nearest neighbor data structures improve searching performance on metric spaces common to robot motion planning problems, while providing asymptotic wait-free concurrent operation. Cache-aware operation avoids long memory access times, allowing the algorithm to exhibit superlinear speedup. Split robot-cloud computation enables robots with low-power CPUs to react to changing environments by having the robot compute reactive paths in real-time from a set of motion plan options generated in a computationally intensive cloud-based algorithm. We demonstrate the scalability and effectiveness of our contributions in solving motion planning problems both in simulation and on physical robots of varying design and complexity. Problems include finding a solution to a complex motion planning problem, pre-computing motion plans that converge towards the optimal, and reactive interaction with dynamic environments. Robots include 2D holonomic robots, 3D rigid-body robots, a self-driving 1/10 scale car, articulated robot arms with and without mobile bases, and a small humanoid robot.Doctor of Philosoph

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

The nature and significance of the response latency associated with the amendment of movements of varying complexity

This investigation examined variation in the reaction time (RT2) to the second of two closely paired stimuli when responses were ordered according to relative degree of movement complexity. The sequences included: (a) executing a simple response following a simple response, (b) executing a complex response following a simple response, (c) executing a simple response following a complex response and (d) executing a complex response following a complex response. The interstimulus intervals were also varied over selected periods of 100, 200, 400, and 800 milliseconds for the purpose of requiring subjects to amend their initial responses at differing points of implementation. An additional question investigated was whether a relationship existed between reaction time measured in a single task situation and RT2. Measures of reaction time on single and sequential response tasks were generated from 24, female, right-handed volunteers from the University of North Carolina in Greensboro. Subjects were required to attend sessions on five different days

A software classification scheme

Reusing code is one approach to software reusability. Code is the end product of the software lifecycle. It is delivered in a low level representation that is difficult to reuse unless an almost perfect match exists between available features and required specifications. There is a need to organize large inventories of software such that reusable code is easy to locate and exchange. The relative success in the reuse of code fragments reported by some software factories is due in part to their capacity to encapsulate domain specific functions and create specialized libraries of components classified by these locally standardized functions.A general software classification scheme that organizes reusability related attributes and common functions from different domains is proposed as a partial solution to the software reusability problem. For the problem of selecting from similar, potentially reusable. components, a partial solution based on evaluation of common characteristics is also proposed. A library system is presented that integrates the proposed classification scheme with an evaluation mechanism based on inherent component attributes, programming languages characteristics and reuser experience.The fundamental contribution of this dissertation is a formal treatment of a faceted scheme for software classification leading to better understanding of reusability at the code level. This approach has been prototyped in a library system for the semi-automatic classification of software components. Analysis were performed to evaluate the classification scheme. The results show the potential of the scheme in organizing collections of code fragments, in improving retrieval, and in simplifying the classification process. Tests of the evaluation mechanism showed positive correlation with evaluations conducted by potential reusers

Shared-Use Bus Priority Lanes On City Streets: Case Studies in Design and Management, MTI Report 11-10

This report examines the policies and strategies governing the design and, especially, operations of bus lanes in major congested urban centers. It focuses on bus lanes that operate in mixed traffic conditions; the study does not examine practices concerning bus priority lanes on urban highways or freeways. Four key questions addressed in the paper are: How do the many public agencies within any city region that share authority over different aspects of the bus lanes coordinate their work in designing, operating, and enforcing the lanes? What is the physical design of the lanes? What is the scope of the priority use granted to buses? When is bus priority in effect, and what other users may share the lanes during these times? How are the lanes enforced? To answer these questions, the study developed detailed cases on the bus lane development and management strategies in seven cities that currently have shared-use bus priority lanes: Los Angeles, London, New York City, Paris, San Francisco, Seoul, and Sydney. Through the case studies, the paper examines the range of practices in use, thus providing planners and decision makers with an awareness of the wide variety of design and operational options available to them. In addition, the report highlights innovative practices that contribute to bus lanes’ success, where the research findings make this possible, such as mechanisms for integrating or jointly managing bus lane planning and operations across agencies

Hidden in Plain Sight: Tehran\u27s Empowering Protean Spaces

As a recent citizen I noticed Tehran\u27s urge for new kinds of public spaces. So, I initiated a dissertation that outlined a call for protean space. Cities need protean spaces as a means to empower people, places that offer social interaction and support--spaces that are safe, accessible, and intriguing. Protean spaces empower people to create places for personal and interpersonal relationships, make social connections, gain information, and build trust across varied networks. My dissertation examined how planning and design practices can enhance the possibility of protean spaces and therefore increase their number. While my research concerns Tehran, all cities benefit from their creation. Professionals can foster the creation if they could consider the ad hoc ways people--over time and within a given site--create opportunities for self-growth and human contact. Tehran lacks accessible and welcoming public spaces and suffers from inadequate, inflexible, and expensive housing. To renew Tehran\u27s public spaces, my dissertation mapped Tehran\u27s marginal possibilities in unconventional urban territories, in the natural residues, ordinary streets, and domestic zones. There, I suggest alternative ways of recycling the city\u27s fragmented space to foster protean spaces. I studied alternative processes that could enhance and increase protean spaces there. The process draws inspirations from how Tehranis have made places, for example, in patoghs. The process can accommodate Tehranis with better protean spaces for future adaptations. Protean space opportunities exist at the intra-city residual natural landscapes: the leftover green patches on the Alborz Mountain ridges, half-erased river-valley corridors, and underground matrix of abandoned qanats. These sites are currently disconnected from the city\u27s structure and its people. Mundane sidewalks--readily available, fully public, and free of charge--are opportunity sites. Due to the deficiency and hostility of public spaces, people appropriate sidewalks as ad hoc meeting places, but most sidewalks produce uninteresting and clichéd experiences. Average houses are private sites with public space design possibilities. Tehran\u27s housing crisis has produced inadequate and pricey homes, often poorly constructed and of singularly uninspired design. Despite being unexciting and lacking identity, they offer leftover space possibilities between, below, atop, and inside that could be repurposed

Three Essays on the Management of Local Government Cash Flows

This dissertation is composed of three essays which evaluate financial strategies used to manage cash flows and the broader working capital management process in local governments. The objective of this dissertation is to address unresolved questions in the literature regarding the use of short-term financial resources to improve a government’s internal operating process and successfully navigate challenging fiscal environments. Together, the three essays contribute to our understanding of cash flow management strategies and the consequences of their implementation in United States local governments. The first essay, in Chapter 2, evaluates the motivating factors that encourage managers to use an external financing source, short-term debt. This research, conducted in collaboration with Professor Sharon N. Kioko, is the first empirical investigation of the factors that promote short-term debt use by a wide range of local governments. It is hypothesized that managers can issue short-term debt as one financial strategy to reduce financial uncertainty from the timing of cash receipts, expenditure flexibility, and favorable long-term debt market conditions. On the basis of data examined between 1996 and 2016 from a heterogeneous sample of New York general purpose governments, evidence suggests that fewer cash assets, a declining prior year budget surplus, higher proportions of federal aid, increases in salary and wages expenditures, more capital spending, as well as more use of long-term debt for bridge financing increase the likelihood of using short-term debt. These results, in turn, imply that managers need to be responsive to changes in the composition of short-term assets and revenues, and understand the cash flow implications of changes in operations, revenue projections, and budgetary spending flexibility. These findings both add to our knowledge of the factors that influence the use of one external source of financing as well as motivate curiosity about alternative strategies used by managers. The second essay, in Chapter 3, extends our knowledge by evaluating various financial strategies that rely on internal resources and external sources of financing used throughout the working capital management process. Strategies that rely on internal resources (e.g., unrestricted cash, savings, interfund borrowing, interfund transfers, and delaying payments) and external sources of financing (e.g., speeding up collections of receivables, accessing a line of credit, direct lending, and issuing short-term debt) are used to mitigate cash deficits and promote sustained operations. In this first examination of the preference and use of public working capital management strategies, it is asserted that managers have a pecking order, or preference ranking, for strategies that use internal resources before external sources of financing. Using a 2016 survey of financial managers in New York local governments, findings suggest managers have a preference ranking for reducing unrestricted cash before delaying payments, speeding up the collections of receivables, issuing short-term debt, and not taking any action to mitigate cash flow uncertainty. Managers most often implement strategies that combine the use of unrestricted cash and short-term debt. Yet, rule-based policies and operating procedures regarding these resources lack sufficient development. Ultimately, a more complete understanding of financial strategies used for public working capital management is advanced. However, the extent to which these strategies can be impacted by the broader economic and fiscal environment can be explored in future research. The third essay, in Chapter 4, asserts that the slack resource of excess taxing capacity influences the use of short-term resources. Specifically, this study systematically examines if excess taxing capacity (the difference between the levy limit and selected property tax level subject to the limit) impacts General Fund unrestricted cash and short-term borrowing. Using panel data from New York local governments between 1996 and 2016, I find suggestive evidence managers are more likely to reduce cash holdings and engage in short-term borrowing when excess taxing capacity increases. The implications of these findings are that managers likely leverage their internal cash and short-term borrowing capacity to accumulate external slack of their property taxing authority. Local government managers, therefore, are being prudent to not hoard cash and borrow in the short-term instead of continually utilizing more of their taxing authority. Overall, the findings represent an important addition to our knowledge of how a more visible slack resource, excess taxing capacity, influences the use of slack resources that are exclusively within the discretion of government managers, short-term resources

Natural Language Generation as an Intelligent Activity (Proposal for Dissertation Research)

In this proposal, I outline a generator conceived of as part of a general intelligent agent. The generator\u27s task is to provide the overall system with the ability to use communication in language to serve its purposes, rather than to simply encode information in language. This requires that generation be viewed as a kind of goal-directed action that is planned and executed in a dynamically changing environment. In addition, the generator must not be dependent on domain or problem-specific information but rather on a general knowledge base .that it shares with the overall system. These requirements have specific consequences for the design of the generator and the representation it uses. In particular, the text planner and the low-level linguistic component must be able to interact and negotiate over decisions that involve both high-level and low-level constraints. Also, the knowledge representation must allow for the varying perspective that an intelligent agent will have on the things it talks about; the generator must be able to appropriately vary how it describes things as the system\u27s perspective on them changes. The generator described here will demonstrate how these ideas work in practice and develop them further