Testing and Active Learning of Resettable Finite-State Machines

This thesis proposes novel active-learning algorithms and testing methods for deterministic finite-state machines that (i) have a specified transition from every state on each input of the (fixed) alphabet and (ii) can be reliably reset to the initial state on request. These algorithms rely on the novel methods of construction of separating sequences. Extensive evaluation demonstrates that the described testing and learning methods are the most efficient in terms of the amount of interaction by a tester with the system under test

Developments in Stochastic Fuel Efficient Cruise Control and Constrained Control with Applications to Aircraft.

This dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed and uses the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns, often referred to as pulse and glide (PnG). Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. A practical implementation strategy of these patterns is then developed and demonstrated. Also, several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. An approach to constrained flight planning based on chaining recoverable sets or integral safe sets is described and illustrated with a simulation example. Finally, two control schemes that exploit integral safe sets are proposed. The first scheme, referred to as the controller state governor (CSG), resets the controller state (typically an integrator) to enforce the constraints and enlarge the set of plant states that can be recovered without constraint violation. The second scheme, referred to as the controller state and reference governor (CSRG), combines the controller state governor with the reference governor control architecture and provides the capability of simultaneously modifying the reference command and the controller state to enforce the constraints. Theoretical results that characterize the response properties of both schemes are presented. Examples are reported that illustrate the operation of these schemes.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111399/1/kevinmcd_1.pd

Off-Policy Evaluation of Probabilistic Identity Data in Lookalike Modeling

We evaluate the impact of probabilistically-constructed digital identity data collected from Sep. to Dec. 2017 (approx.), in the context of Lookalike-targeted campaigns. The backbone of this study is a large set of probabilistically-constructed "identities", represented as small bags of cookies and mobile ad identifiers with associated metadata, that are likely all owned by the same underlying user. The identity data allows to generate "identity-based", rather than "identifier-based", user models, giving a fuller picture of the interests of the users underlying the identifiers. We employ off-policy techniques to evaluate the potential of identity-powered lookalike models without incurring the risk of allowing untested models to direct large amounts of ad spend or the large cost of performing A/B tests. We add to historical work on off-policy evaluation by noting a significant type of "finite-sample bias" that occurs for studies combining modestly-sized datasets and evaluation metrics involving rare events (e.g., conversions). We illustrate this bias using a simulation study that later informs the handling of inverse propensity weights in our analyses on real data. We demonstrate significant lift in identity-powered lookalikes versus an identity-ignorant baseline: on average ~70% lift in conversion rate. This rises to factors of ~(4-32)x for identifiers having little data themselves, but that can be inferred to belong to users with substantial data to aggregate across identifiers. This implies that identity-powered user modeling is especially important in the context of identifiers having very short lifespans (i.e., frequently churned cookies). Our work motivates and informs the use of probabilistically-constructed identities in marketing. It also deepens the canon of examples in which off-policy learning has been employed to evaluate the complex systems of the internet economy.Comment: Accepted by WSDM 201

Universal semantic communication

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 325-334).Is meaningful communication possible between two intelligent parties who share no common language or background? We propose that this problem can be rigorously addressed by explicitly focusing on the goals of the communication. We propose a theoretical framework in which we can address when and to what extent such semantic communication is possible. Our starting point is a mathematical definition of a generic goal for communication, that is pursued by agents of bounded computational complexity. We then model a "lack of common language or background" by considering a class of potential partners for communication; in general, this formalism is rich enough to handle varying degrees of common language and backgrounds, but the complete lack of knowledge is modeled by simply considering the class of all partners with which some agent of similar power could achieve our goal. In this formalism, we will find that for many goals (but not all), communication without any common language or background is possible. We call the strategies for achieving goals without relying on such background universal protocols. The main intermediate notions introduced by our theory are formal notions of feedback that we call sensing. We show that sensing captures the essence of whether or not reliable universal protocols can be constructed in many natural settings of interest: we find that across settings, sensing is almost always sufficient, usually necessary, and generally a useful design principle for the construction of universal protocols. We support this last point by developing a number of examples of protocols for specific goals. Notably, we show that universal delegation of computation from a space-efficient client to a general-purpose server is possible, and we show how a variant of TCP can allow end-users on a packet network to automatically adapt to small changes in the packet format (e.g., changes in IP). The latter example above alludes to our main motivation for considering such problems, which is to develop techniques for modeling and constructing computer systems that do not require that their components strictly adhere to protocols: said differently, we hope to be able to design components that function properly with a sufficiently wide range of other components to permit a rich space of "backwards-compatible" designs for those components. We expect that in the long run, this paradigm will lead to simpler systems because "backwards compatibility" is no longer such a severe constraint, and we expect it to lead to more robust systems, partially because the components should be simpler, and partially because such components are inherently robust to deviations from any fixed protocol. Unfortunately, we find that the techniques for communication under the complete absence of any common background suffer from overhead that is too severe for such practical purposes, so we consider two natural approaches for introducing some assumed common background between components while retaining some nontrivial amount of flexibility. The first approach supposes that the designer of a component has some "belief" about what protocols would be "natural" to use to interact with other components; we show that, given sensing and some sufficient "agreement" between the beliefs of the designers of two components, the components can be made universal with some relatively modest overhead. The second approach supposes that the protocols are taken from some restricted class of functions, and we will see that for certain classes of functions and simple goals, efficient universal protocols can again be constructed from sensing. Actually, we show more: the special case of our model described in the second approach above corresponds precisely to the well-known model of mistake-bounded on-line learning first studied by Barzdirs and Frievalds, and later considered in more depth by Littlestone. This connection provides a reasonably complete picture of the conditions under which we can apply the second approach. Furthermore, it also seems that the first approach is closely related to the problem of designing good user interfaces in Human-Computer Interaction. We conclude by briefly sketching the connection, and suggest that further development of this connection may be a potentially fruitful direction for future work.by Brendan Juba.Ph.D

Introduction to Communication Systems Using National Instruments Universal Software Peripheral Radio Lab Manual

The students at the University of New Mexico Electrical and Computer Engineering Department are planning to use an integrated set of lectures and labs to better understand basic communications systems. The lectures are based on the textbook by Ziemer and Tranter, Principles of Communications - Systems, Modulation, and Noise. The labs are developed using the National Instruments Universal Software Radio Peripheral (USRP). The choice of this radio provides 2 advantages from an instructional perspective: it minimizes the amount of lab equipment necessary for performing the labs, and its range of flexibility to support spectrum sensing, cognitive radio and alternate modulation schemes. (Párrafo extraído del texto a modo de resumen)Ibero-American Science and Technology Education Consortium (ISTEC

Model-based integration testing technique using formal finite state behavioral models for component-based software

Many issues and challenges could be identified when considering integration testing of Component-Based Software Systems (CBSS). Consequently, several research have appeared in the literature, aimed at facilitating the integration testing of CBSS. Unfortunately, they suffer from a number of drawbacks and limitations such as difficulty of understanding and describing the behavior of integrated components, lack of effective formalism for test information, difficulty of analyzing and validating the integrated components, and exposing the components implementation by providing semi-formal models. Hence, these problems have made it in effective to test today’s modern complex CBSS. To address these problems, a model-based approach such as Model-Based Testing (MBT) tends to be a suitable mechanism and could be a potential solution to be applied in the context of integration testing of CBSS. Accordingly, this thesis presents a model-based integration testing technique for CBSS. Firstly, a method to extract the formal finite state behavioral models of integrated software components using Mealy machine models was developed. The extracted formal models were used to detect faulty interactions (integration bugs) or compositional problems between integrated components in the system. Based on the experimental results, the proposed method had significant impact in reducing the number of output queries required to extract the formal models of integrated software components and its performance was 50% better compared to the existing methods. Secondly, based on the extracted formal models, an effective model-based integration testing technique (MITT) for CBSS was developed. Finally, the effectiveness of the MITT was demonstrated by employing it in the air gourmet and elevator case studies, using three evaluation parameters. The experimental results showed that the MITT was effective and outperformed Shahbaz technique on the air gourmet and elevator case studies. In terms of learned components for air gourmet and elevator case studies respectively, the MITT results were better by 98.14% and 100%, output queries based on performance were 42.13% and 25.01%, and error detection capabilities were 70.62% and 75% for each of the case study

Introduction to Communication Systems Using National Instruments Universal Software Peripheral Radio Lab Manual

The students at the University of New Mexico Electrical and Computer Engineering Department are planning to use an integrated set of lectures and labs to better understand basic communications systems. The lectures are based on the textbook by Ziemer and Tranter, Principles of Communications - Systems, Modulation, and Noise. The labs are developed using the National Instruments Universal Software Radio Peripheral (USRP). The choice of this radio provides 2 advantages from an instructional perspective: it minimizes the amount of lab equipment necessary for performing the labs, and its range of flexibility to support spectrum sensing, cognitive radio and alternate modulation schemes. (Párrafo extraído del texto a modo de resumen)Ibero-American Science and Technology Education Consortium (ISTEC

The Comprehensive Handling of Safety in an Autonomous Robot Capstone Project

A systematic approach to safety issues is described in the context of an autonomous robot capstone project. The treatment of safety should not be an ad hoc or an after-thought aspect of design projects. Engineering students need to consider safety as an integral component of the design process and to identify and address hazards systematically in each stage of project work. Appropriate actions include researching professional standards and regulations, incorporating safety best practices, developing safety checklists and operating protocols, and providing significant safety documentation. Formal safety components were added to a capstone design project for electrical and computer engineering undergraduates in which an R2D2-like robot was designed and built. The work provides project examples, lessons learned, and student feedback related to the safety treatment

Neural dynamics of social behavior : An evolutionary and mechanistic perspective on communication, cooperation, and competition among situated agents

Social behavior can be found on almost every level of life, ranging from microorganisms to human societies. However, explaining the evolutionary emergence of cooperation, communication, or competition still challenges modern biology. The most common approaches to this problem are based on game-theoretic models. The problem is that these models often assume fixed and limited rules and actions that individual agents can choose from, which excludes the dynamical nature of the mechanisms that underlie the behavior of living systems. So far, there exists a lack of convincing modeling approaches to investigate the emergence of social behavior from a mechanistic and evolutionary perspective. Instead of studying animals, the methodology employed in this thesis combines several aspects from alternative approaches to study behavior in a rather novel way. Robotic models are considered as individual agents which are controlled by recurrent neural networks representing non-linear dynamical system. The topology and parameters of these networks are evolved following an open-ended evolution approach, that is, individuals are not evaluated on high-level goals or optimized for specific functions. Instead, agents compete for limited resources to enhance their chance of survival. Further, there is no restriction with respect to how individuals interact with their environment or with each other. As its main objective, this thesis aims at a complementary approach for studying not only the evolution, but also the mechanisms of basic forms of communication. For this purpose it can be shown that a robot does not necessarily have to be as complex as a human, not even as complex as a bacterium. The strength of this approach is that it deals with rather simple, yet complete and situated systems, facing similar real world problems as animals do, such as sensory noise or dynamically changing environments. The experimental part of this thesis is substantiated in a five-part examination. First, self-organized aggregation patterns are discussed. Second, the advantages of evolving decentralized control with respect to behavioral robustness and flexibility is demonstrated. Third, it is shown that only minimalistic local acoustic communication is required to coordinate the behavior of large groups. This is followed by investigations of the evolutionary emergence of communication. Finally, it is shown how already evolved communicative behavior changes during further evolution when a population is confronted with competition about limited environmental resources. All presented experiments entail thorough analysis of the dynamical mechanisms that underlie evolved communication systems, which has not been done so far in the context of cooperative behavior. This framework leads to a better understanding of the relation between intrinsic neurodynamics and observable agent-environment interactions. The results discussed here provide a new perspective on the evolution of cooperation because they deal with aspects largely neglected in traditional approaches, aspects such as embodiment, situatedness, and the dynamical nature of the mechanisms that underlie behavior. For the first time, it can be demonstrated how noise influences specific signaling strategies and that versatile dynamics of very small-scale neural networks embedded in sensory-motor feedback loops give rise to sophisticated forms of communication such as signal coordination, cooperative intraspecific communication, and, most intriguingly, aggressive interspecific signaling. Further, the results demonstrate the development of counteractive niche construction based on a modification of communication strategies which generates an evolutionary feedback resulting in an active reduction of selection pressure, which has not been shown so far. Thus, the novel findings presented here strongly support the complementary nature of robotic experiments to study the evolution and mechanisms of communication and cooperation.</p