Performance Appraisal Research: A Critical Review of Work on “The Social Context and Politics of Appraisal”

This paper reviews existing literatures on the analysis of performance appraisal (PA) paying special attention to those which try to take into account the “social context” of appraisal systems and processes. The special place of political action within these processes is underlined and the different levels at which politics need to be considered in research are outlined. Research on politics is considered and shown to lack an adequate consideration of the social relations involved in the reciprocal interactions between PA tools and processes and users interpretation and manipulation of them.Performance appraisal; Social context; Politics

An agent programming manifesto

There has been considerable progress in both the theory and practice of agent programming since Georgeff & Rao’s seminal work on the Belief-Desire-Intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are confined to a small number of niche areas, and adoption of agent programming languages in mainstream software development remains limited. This state of affairs is widely acknowledged within the community, and a number of reasons and remedies have been proposed. In this paper, I present an analysis of why agent programming has failed to make an impact that is rooted in the class of programming problems agent programming sets out to solve, namely the realisation of flexible intelligent behaviour in dynamic and unpredictable environments. Based on this analysis, I outline some suggestions for the future direction of agent programming, and some principles that I believe any successful future direction must follow

Future directions in agent programming

Agent programming is a subfield of Artificial Intelligence concerned with the development of intelligent autonomous systems that combine multiple capabilities, e.g., sensing, deliberation, problem-solving and action, in a single system. There has been considerable progress in both the theory and practice of agent programming since Georgeff & Rao’s seminal work on the Belief-Desire-Intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are currently confined to a small number of niche areas, and adoption of agent programming languages (APLs) in mainstream software development remains limited. In this paper, I argue that increased adoption of agent programming is contingent on being able to solve a larger class of AI problems with significantly less developer effort than is currently the case, and briefly sketch one possible approach to expanding the set of AI problems that can be addressed by APLs. Critically, the approach I propose requires minimal developer effort and expertise, and relies instead on expanding the basic capabilities of the language

МЕТОД ОЦЕНКИ КВАЛИФИКАЦИИ И ОПТИМИЗАЦИЯ СОСТАВА ПРОФЕССИОНАЛЬНЫХ ГРУПП ПРОГРАММИСТОВ

The problem of building and optimizing the teams of programmers taking into account the qualification and the level of skills in programming technologies and tools is considered. Known technological environments for the management of teamwork, such as Agile, formulate only general requirements and principles for building the teams and the distribution of work between them. A method for formalizing and evaluating the qualification of individual programmers and entire groups of programmers has been proposed. The input data are attributes of the most popular technologies and programming tools, including technology rating, as well as the results of a survey of programmers on their level of skills. The qualification of a group of programmers is evaluated taking into account the requirements for a particular project, which integrates three components: the average qualification of programmers included in the group; the qualification of the group with respect to the best representatives for each of the technologies; threshold values of the levels of programmer qualification and group qualification for each of the technologies, as well as threshold values of the integrated qualification, reflecting the specifics of the given project. The contribution of each component is determined by appropriate weights. The proposed method is a basis for a genetic algorithm that performs the search for the number, size and staff of groups of programmers which yield a maximum of total qualification. Software has been developed and computer experiments have been carried out on a set of programmers who graduated from Belarusian universities. The obtained results demonstrate the real ability of the system to find the number, size and staff of groups of programmers, which increase the overall qualification of groups by 30% while minimizing the number of unemployed developers. The results prove the practical importance of the method and software in the field of technologies and tools for the management of professional teams of programmers.Рассматривается проблема формирования и оптимизации команд программистов с учетом квалификации и уровня владения технологиями и инструментами программирования. Известные технологические среды для организации работы команд, такие как Agile, формулируют лишь общие требования и принципы формирования коллективов и распределения работ между ними. Предлагается метод формализации оценки квалификации отдельных программистов и целых программистских групп. Исходными являются данные о наиболее востребованных технологиях и инструментах программирования, их рейтинге, а также результаты опроса программистов об уровне владения ими. Квалификация группы программистов оценивается с учетом требований к конкретному проекту как величина, интегрирующая три составляющие: среднюю квалификацию программистов, включаемых в группу; квалификацию группы по лучшим представителям по каждой из технологий; пороговые значения уровней квалификации программистов и групп программистов по каждой из технологий, а также пороговые значения интегрированной квалификации, отражающие специфику конкретного проекта. Вклад каждой составляющей определяется варьируемыми. весовыми коэффициентами. Метод положен в основу генетического алгоритма, выполняющего поиск количества, размера и состава программистских групп, которые имеют максимальную суммарную квалификацию. Разработано программное обеспечение и проведены вычислительные эксперименты на выборке программистов, окончивших белорусские университеты. Полученные результаты демонстрируют реальную способность системы находить количество, состав и размеры групп программистов, увеличивающие суммарную квалификации групп до 30% при минимизации числа незадействованных разработчиков. Результаты доказывают практическую значимость разработки в сфере технологий и средств управления профессиональными коллективами программистов

Ηαγεμονία: A New Treaty from Classical Thebes

Die Autoren legen die Erstedition einer Inschrift vor, die bei einer Notgrabung in Theben südlich der Kadmeia nahe bei den Toren der Elektra gefunden wurde. Die in der epichorischen Schrift von Böotien geschriebene Inschrift kann ins 4. Jh. v.Chr. datiert werden. Sie enthält das Ende eines Vertrags zwischen Theben und Histiaia, der den Thebanern die Führung in einem Krieg (hαγεμονία) zuspricht. Aus paläographischen und historischen Gründen erwägen die Autoren ein Datum in den 370er oder 360er Jahren, bevorzugen aber eine Datierung um 377 v.Chr., als die Thebaner nach Xenophon die Akropolis von Histiaia einnehmen konnten, die bis dahin unter der Kontrolle Spartas gestanden hatte. Die Autoren diskutieren auch die Möglichkeit, dass der Vertrag ursprünglich im Heiligtum des Herakles, der Stadtgottheit von Theben, ausgestellt war.The authors present the editio princeps of an inscribed document found in a rescue excavation at Thebes, in the area immediately to the south of Kadmeia, near the Electran Gates. The inscription, written in the epichoric script of Boeotia, can be dated to the early 4th c. BC. It preserves the end of a treaty between Thebes and Histiaia which assigns war leadership (hαγεμονία) to the Thebans. By virtue of historical and paleographical analysis, they consider a date in the 370s or the 360s, but express their preference for a date ca. 377 BC when, according to Xenophon, the Thebans managed to seize the acropolis of Histiaia which had been under Spartan control. The authors also explore the possibility that the treaty was originally displayed in the shrine of Herakles, the poliadic divinity of Thebes.Les auteurs présentent l’editio princeps d’un document inscrit trouvé lors de fouilles préventives à Thèbes, dans la région immédiatement au sud de Cadmée, près des Portes Électrides. Inscrite en caractères épichoriques de Béotie, l’inscription peut être datée du début du 4e s.a.C. Elle préserve la fin d’un traité entre Thèbes et Histiaia qui assigne la conduite de la guerre (hαγεμονία) aux Thébains. L’analyse historique et paléographique indiquerait une datation dans les années 370 ou 360, mais les auteurs préfèrent dater vers 377 a.C. quand, selon Xénophon, les Thébains réussirent à s’emparer de l’acropole d’Histiée qui était jusque là sous contrôle lacédémonien. Ils explorent aussi la possibilité que le traité était à l’origine exposé dans le sanctuaire d’Héraclès, la divinité poliade de Thèbes

Contributions to artificial intelligence: the IIIA perspective

La intel·ligència artificial (IA) és un camp científic i tecnològic relativament nou dedicat a l'estudi de la intel·ligència mitjançant l'ús d'ordinadors com a eines per produir comportament intel·ligent. Inicialment, l'objectiu era essencialment científic: assolir una millor comprensió de la intel·ligència humana. Aquest objectiu ha estat, i encara és, el dels investigadors en ciència cognitiva. Dissortadament, aquest fascinant però ambiciós objectiu és encara molt lluny de ser assolit i ni tan sols podem dir que ens hi haguem acostat significativament. Afortunadament, però, la IA també persegueix un objectiu més aplicat: construir sistemes que ens resultin útils encara que la intel·ligència artificial de què estiguin dotats no tingui res a veure amb la intel·ligència humana i, per tant, aquests sistemes no ens proporcionarien necessàriament informació útil sobre la naturalesa de la intel·ligència humana. Aquest objectiu, que s'emmarca més aviat dins de l'àmbit de l'enginyeria, és actualment el que predomina entre els investigadors en IA i ja ha donat resultats impresionants, tan teòrics com aplicats, en moltíssims dominis d'aplicació. A més, avui dia, els productes i les aplicacions al voltant de la IA representen un mercat anual de desenes de milers de milions de dòlars. Aquest article resumeix les principals contribucions a la IA fetes pels investigadors de l'Institut d'Investigació en Intel·ligència Artificial del Consell Superior d'Investigacions Científiques durant els darrers cinc anys.Artificial intelligence is a relatively new scientific and technological field which studies the nature of intelligence by using computers to produce intelligent behaviour. Initially, the main goal was a purely scientific one, understanding human intelligence, and this remains the aim of cognitive scientists. Unfortunately, such an ambitious and fascinating goal is not only far from being achieved but has yet to be satisfactorily approached. Fortunately, however, artificial intelligence also has an engineering goal: building systems that are useful to people even if the intelligence of such systems has no relation whatsoever with human intelligence, and therefore being able to build them does not necessarily provide any insight into the nature of human intelligence. This engineering goal has become the predominant one among artificial intelligence researchers and has produced impressive results, ranging from knowledge-based systems to autonomous robots, that have been applied to many different domains. Furthermore, artificial intelligence products and services today represent an annual market of tens of billions of dollars worldwide. This article summarizes the main contributions to the field of artificial intelligence made at the IIIA-CSIC (Artificial Intelligence Research Institute of the Spanish Scientific Research Council) over the last five years

PROFESSIONAL DEVELOPMENT OF TURKISH PRESCHOOL TEACHERS DURING SUMMER HOLIDAYS

The purpose of this study is to examine the professional development of preschool teachers during summer holidays, and to develop recommendations for professional development between teaching semesters. The study is built on the basic interpretive design, with a study group of 24 preschool teachers. The data were collected through semi-structured interviews and were analyzed through content analysis. The content analysis revealed that summer holidays are basically seen as getting away from the profession and relaxation for preschool teachers, not as an opportunity for professional development. Preschool teachers found summer holidays unproductive in terms of their professional development. While the preschool teachers think that professional development activities should exist during the summer holidays, they believe that the current professional development system in Turkey does not make the idea very attractive and is considered to be efficient. The preschool teachers recommended that all professional development activities should fit with the needs of teachers, that both their personal and professional development should be supported, that holistic content should be created, that instructors specialized should be recruited, that learning methods fostering active participation and alternative assessment methods should be preferred, and that the expertise gained through professional development should be recognized, and rewarded

An agent programming manifesto

There has been considerable progress in both the theory and practice of agent programming since Georgeff & Rao’s seminal work on the Belief-Desire-Intention paradigm. However, despite increasing interest in the development of autonomous systems, applications of agent programming are confined to a small number of niche areas, and adoption of agent programming languages in mainstream software development remains limited. This state of affairs is widely acknowledged within the community, and a number of reasons and remedies have been proposed. In this paper, I present an analysis of why agent programming has failed to make an impact that is rooted in the class of programming problems agent programming sets out to solve, namely the realisation of flexible intelligent behaviour in dynamic and unpredictable environments. Based on this analysis, I outline some suggestions for the future direction of agent programming, and some principles that I believe any successful future direction must follow

Agent programming in the cognitive era

It is claimed that, in the nascent ‘Cognitive Era’, intelligent systems will be trained using machine learning techniques rather than programmed by software developers. A contrary point of view argues that machine learning has limitations, and, taken in isolation, cannot form the basis of autonomous systems capable of intelligent behaviour in complex environments. In this paper, we explore the contributions that agent-oriented programming can make to the development of future intelligent systems. We briefly review the state of the art in agent programming, focussing particularly on BDI-based agent programming languages, and discuss previous work on integrating AI techniques (including machine learning) in agent-oriented programming. We argue that the unique strengths of BDI agent languages provide an ideal framework for integrating the wide range of AI capabilities necessary for progress towards the next-generation of intelligent systems. We identify a range of possible approaches to integrating AI into a BDI agent architecture. Some of these approaches, e.g., ‘AI as a service’, exploit immediate synergies between rapidly maturing AI techniques and agent programming, while others, e.g., ‘AI embedded into agents’ raise more fundamental research questions, and we sketch a programme of research directed towards identifying the most appropriate ways of integrating AI capabilities into agent programs