Entropy-based strategies for physical exploration of the environment's degrees of freedom

Abstract — Physical exploration refers to the challenge of autonomously discovering and learning how to manipulate the environment’s degrees of freedom (DOF)—by identifying promising points of interaction and pushing or pulling object parts to reveal DOF and their properties. Recent existing work focused on sub-problems like estimating DOF parameters from given data. Here, we address the integrated problem, focusing on the higher-level strategy to iteratively decide on the next exploration point before applying motion generation methods to execute the explorative action and data analysis methods to interpret the feedback. We propose to decide on exploration points based on the expected information gain, or change in entropy in the robot’s current belief (uncertain knowledge) about the DOF. To this end, we first define how we represent such a belief. This requires dealing with the fact that the robot initially does not know which random variables (which DOF, and depending on their type, which DOF properties) actually exist. We then propose methods to estimate the expected information gain for an exploratory action. We analyze these strategies in simple environments and evaluate them in combination with full motion planning and data analysis in a physical simulation environment. I

Environmental management in development : the evolution of paradigms

In the past quarter century, environmental management has increasingly become a concern of governments. More recently, the traditional split between developers and conservationists has begun to break down. Conceptions of what is economically and technologically practical, ecologically necessary, and politically feasible are rapidly changing. This report discusses the implications of five paradigms of environmental management in development. The author notes that the remedial legalistic approach of environmental management is breaking down. Instead, interest in the more economically integrated approach of resource management has recently taken hold. Several interdependent forces indicate that improving the economic management of pollution and resources may be a necessary but insufficient measure to create the conditions for sustainable development. The perception of tradeoffs between development and environmental quality persists in the present debate, but its necessity is greatly exaggerated, according to this paper. Finally, it is noted that paradigms may be impervious to evidence, and institutions and societies too difficult to change. Whether, when and how these issues are resolved may be modern civilization's most significant test.Environmental Economics&Policies,Agricultural Knowledge&Information Systems,Health Monitoring&Evaluation,Natural Resources Management,Agricultural Research

The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

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

Sustainability, Distribution, and the Macroeconomic Analysis of Law

Legal economic analysis has traditionally focused on the application of microeconomic theory to questions of legal import. Scholars have generally regarded macroeconomic effects of legal rules as lying beyond the purview of the legal decisiomnaker\u27s jurisdiction. This Article argues that such exclusion of macroeconomic subject matter from legal analysis may rest on a scientifically erroneous view of - the economic process. The conventional understanding of the economic process presumes an unlimited supply of material inputs and an infinite natural capacity to absorb waste outputs. Fundamental scientific principles suggest that this understanding is flawed. The economic process must necessarily be limited in scale by the capacity of the ecological superstructure to sustain it. Thus, in addition td the efficient allocation of resources, legal economic analysis also should be concerned with the sustainable maintenance of scale. Consideration of scale effects by legal decisionmakers cannot be safely ignored in the way that distributive effects have been, given that no political mechanism analogous to the tax and transfer system exists to regulate the scale of the macroeconomy

Enhancement of precise underwater object localization

Underwater communication applications extensively use localization services for object identification. Because of their significant impact on ocean exploration and monitoring, underwater wireless sensor networks (UWSN) are becoming increasingly popular, and acoustic communications have largely overtaken radio frequency (RF) broadcasts as the dominant means of communication. The two localization methods that are most frequently employed are those that estimate the angle of arrival (AOA) and the time difference of arrival (TDoA). The military and civilian sectors rely heavily on UWSN for object identification in the underwater environment. As a result, there is a need in UWSN for an accurate localization technique that accounts for dynamic nature of the underwater environment. Time and position data are the two key parameters to accurately define the position of an object. Moreover, due to climate change there is now a need to constrain energy consumption by UWSN to limit carbon emission to meet net-zero target by 2050. To meet these challenges, we have developed an efficient localization algorithm for determining an object position based on the angle and distance of arrival of beacon signals. We have considered the factors like sensor nodes not being in time sync with each other and the fact that the speed of sound varies in water. Our simulation results show that the proposed approach can achieve great localization accuracy while accounting for temporal synchronization inaccuracies. When compared to existing localization approaches, the mean estimation error (MEE) and energy consumption figures, the proposed approach outperforms them. The MEEs is shown to vary between 84.2154m and 93.8275m for four trials, 61.2256m and 92.7956m for eight trials, and 42.6584m and 119.5228m for twelve trials. Comparatively, the distance-based measurements show higher accuracy than the angle-based measurements

An outline theory of art on cybernetic principles

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The object of this study is to draw art into the common net of organization, along with those other enterprizes more commonly associated with the exercise of intelligence. The method chosen for this is based upon the idea of effective procedures, namely by setting out to construct a (notional) 'art machine'. The argument falls into two parts, the first dealing with the general concept of authorship and the second with its products. Part I offers a definition of an abstract, rudimentary productive process and describes its observers. There is an examination of the relation between structure and purpose, which moves towards a general definition of authorship made in terms of extracting order from a surrounding. Principles of order extraction are examined, with particular reference to the Law of Requisite Variety. Examination of extracted order, as structure, heuristics and the like, leads to discussion of the transmission of purposes between purposeful systems, as well as general problems of constraint, and of regulation and control. Part I ends with a proposal for a paradigm for a rudimentary mechanical author. Part II concentrates on the products of authorship, seeking characterizing features of those that may be classified as art. There is discussion of objective knowledge and its value and of the characteristics of experience as a form of objective knowledge. It is suggested that art is concerned with experience and that this dictates its method, which is to produce simulation procedures based on a language constituted by the synthetic structures discussed in Part I. Lines are suggested for realizing an 'art machine' and there is a review of prospects. A section of notes consisting of speculative ideas and empirical applications connected with the conclusions of the text follows Part II

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

A multi-dimensional entropy model of jazz improvisation for music information retrieval.

Jazz improvisation provides a case context for examining information in music; entropy provides a means for representing music for retrieval. Entropy measures are shown to distinguish between different improvisations on the same theme, thus demonstrating their potential for representing jazz information for analysis and retrieval. The calculated entropy measures are calibrated against human representation by means of a case study of an advanced jazz improvisation course, in which synonyms for "entropy" are frequently used by the instructor. The data sets are examined for insights in music information retrieval, music information behavior, and music representation