C4.5: Programs for Machine Learning (書評)

When I started out as a newly hatched PhD student, back in the day, one of the first articles I read and understood (or at least thought that I understood) was Ray Reiter’s classic article on default logic (Reiter, 1980).This was some years after the famous ‘non-monotonic logic’ issue of Artificial Intelligence in which that article appeared, but default logic was still one of the leading approaches, a tribute to the simplicity and power of the theory. As a result of reading the article, I became fascinated by both default logic and, more generally, non-monotonic logics. However, despite my fascination, these approaches never seemed terribly useful for the kinds of problem that I was supposed to be studying—problems like those in medical decision making—and so I eventually lost interest. In fact non-monotonic logics seemed to me, and to many people at the time I think, not to be terribly useful for anything. They were interesting, and clearly relevant to the long-term goals of Artificial Intelligence as a discipline, but not of any immediate practical importance. This verdict, delivered at the end of the 1980s, continued, I think, to be true for the next few years while researchers working in non-monotonic logics studied problems that to outsiders seemed to be ever more obscure. However, by the end of the 1990s, it was becoming clear, even to folk as short-sighted as I, that non-monotonic logics were getting to the point at which they could be used to solve practical problems. Knowledge in action shows quite how far these techniques have come. The reason that non-monotonic logics were invented was, of course, in order to use logic to reason about the world. Our knowledge of the world is typically incomplete, and so, in order to reason about it, one has to make assumptions about things one does not know. This, in turn, requires mechanisms for both making assumptions and then retracting them if and when they turn out not to be true. Non-monotonic logics are intended to handle this kind of assumption making and retracting, providing a mechanism that has the clean semantics of logic, but which has a non-monotonic set of conclusions. Much of the early work on non-monotonic logics was concerned with theoretical reasoning, that is reasoning about the beliefs of an agent—what the agent believes to be true. Theoretical reasoning is the domain of all those famous examples like ‘Typically birds fly. Tweety is a bird, so does Tweety fly?’, and the fact that so much of non-monotonic reasoning seemed to focus on theoretical reasoning was why I lost interest in it. I became much more concerned with practical reasoning—that is reasoning about what an agent should do—and non-monotonic reasoning seemed to me to have nothing interesting to say about practical reasoning. Of course I was wrong. When one tries to formulate any kind of description of the world as the basis for planning, one immediately runs into applications of non-monotonic logics, for example in keeping track of the state of a changing world. It is this use of non-monotonic logic that is at the heart of Knowledge in action. Building on the McCarthy’s situation calculus, Knowledge in action constructs a theory of action that encompasses a very large part of what an agent requires to reason about the world. As Reiter says in the final chapter,

Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems

The paper is a overview of the major qualitative spatial representation and reasoning techniques. We survey the main aspects of the representation of qualitative knowledge including ontological aspects, topology, distance, orientation and shape. We also consider qualitative spatial reasoning including reasoning about spatial change. Finally there is a discussion of theoretical results and a glimpse of future work. The paper is a revised and condensed version of [33,34].

Qualitative Spatial Representation and Reasoning: An Overview

Scheduling, vehicle routing and timetabling are all examples of constraint problems, and methods to solve them rely on the idea of constraint propagation and search. This book meets the need for a modern, multidisciplinary introduction to the field that covers foundations and applications. Written by Krzysztof Apt, an authority on the subject, it will be welcomed by graduate students and professionals. With the insertion of constraint techniques into programming environments, new developments have accelerated the solution process. Constraint programming combines ideas from artificial intelligence, programming languages, databases, and operational research.

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Principles of constraint programming

Emotions have an important role in daily life, not only in human interaction, but also in decision-making processes, and in the perception of the world around us. Due to the recent interest shown by the research community in establishing emotional interactions between humans and computers, the identification of the emotional state of the former became a need. This can be achieved through multiple measures, such as subjective self-reports, autonomic and neurophysiological measurements. In the last years, Electroencephalography (EEG) received considerable attention from researchers, since it can provide a simple, cheap, portable, and ease-to-use solution for identifying emotions. In this paper, we present a survey of the neurophysiological research performed from 2009 to 2016, providing a comprehensive overview of the existing works in emotion recognition using EEG signals. We focus our analysis in the main aspects involved in the recognition process (e.g., subjects, features extracted, classifiers), and compare the works per them. From this analysis, we propose a set of good practice recommendations that researchers must follow to achieve reproducible, replicable, well-validated and high-quality results. We intend this survey to be useful for the research community working on emotion recognition through EEG signals, and in particular for those entering this field of research, since it offers a structured starting point.

Emotions Recognition Using EEG Signals: A Survey

Self-localization the correlation of current and former impressions of the world is an essential ability for most mobile agents. In an inhabited dynamic system, high precision metric approaches demand accurate sensor devices and large computational power. In contrast, during the last few years qualitative methods have been explored to overcome mainly problems regarding complexity and stability. This paper describes a qualitative approach to self-localization. With space-time as the ontological primitive and using distinct spatiotemporal patterns for categories of objects, selflocalization within an integrated spatio-temporal framework is investigated. Given a record of local surveys, we show how space-time history descriptions might be abduced from local surveys and spatio-temporal patterns. The qualitative mereotopological world model so constructed forms a basis for self-localization. keywords: spatio-temporal reasoning, selflocalization, space-time.

Qualitative Self-Localization using a Spatio-Temporal Ontology: A Preliminary Report

Abstract This paper presents a two layered control architecture - Superior hand control (SHC) followed by Local hand control (LHC) for an extreme upper limb prosthesis. The control architecture is for executing grasping operations involved in 70% of daily living activities. Forearm electromyogram actuated SHC is for recognition of user’s intended grasp. LHC control the fingers to be actuated for the recognized grasp. The finger actuation is controlled through a proportionalintegral- derivative controller customized with fingertip force sensor. LHC controls joint angles and velocities of the fingers in the prosthetic hand. Fingers in the prosthetic hand emulate the dynamic constraints of human hand fingers. The joint angle trajectories and velocity profiles of the prosthetic hand finger are in close approximation to those of the human finger

A Two Layered Control Architecture for Prosthetic Grasping

Tezpur University (TU) Bionic Hand is a biomimetic extreme upper limb prosthesis. The Hand is intended to emulate grasping operations involved during 70% of daily living activities and have been developed using a biomimetic approach. This paper focus on the development of a local hand control for grasping by TU Bionic Hand. Grasp primitives: finger joint angular positions and joint torques are derived through kinematic and dynamic analysis. TU Bionic Hand emulates the grasp types following the dynamic constraints of human hand. The joint angle trajectories and velocity profiles of the Hand finger are in close approximation to those of the human finger.

Local Hand Control for Tezpur University Bionic Hand Grasping

In this chapter, the history of robotics is traced. The emphasis is on highlighting significant moments in robotics history that had far-reaching consequences on the field. A brief presentation of the technical intricacies is followed by highlight of the recent trends. The chapter finally dwells on the direction robotics is surging and poised to change the world in more things than one could possibly imagine.

Robotics: History, Trends, and Future Directions

In this paper, we have presented a formalism for representation of and reasoning about directions in a qualitative way in an egocentric spatial reference frame. Qualitative direction has been separated from dimensionality of spatial objects and as such, the formalism may be used to represent qualitative direction in a dimension-independent way. The formalism uses fewer number of base relations than existing formalisms and granularity can be refined easily. Algorithms for finding composition and converse of base relations have been presented.

Shyamanta M. Hazarika

Papers

Qualitative Self-Localization using a Spatio-Temporal Ontology: A Preliminary Report

A Two Layered Control Architecture for Prosthetic Grasping

Local Hand Control for Tezpur University Bionic Hand Grasping

Robotics: History, Trends, and Future Directions

Qualitative directions in egocentric spatial reference frame