In this chapter, we situate Sweden in an international context focusing on how programming and computational thinking have been introduced into primary and lower-secondary education (grades 1–9 in the Swedish system). Our review shows that the strategies used in different countries have their own pros and cons, and there is no clear evidence establishing that one method is preferable. Moreover, due to a lack of clear guidelines, decisions on how programming is taught, by whom, and when, are commonly made at school level, also in Sweden. This freedom, or burden, to locally decide on how to implement the curriculum has left teachers in a difficult position, where they are to fulfil the requirements of the curriculum without proper training, time, and competence needed. This has naturally had a negative impact on how programming and computational thinking have been and are introduced at schools. Based on the review we provide six recommendations, which posit that to succeed, a much more systematic and holistic approach is needed, addressing the needs of teachers, students, and schools.

As a result of the increased digitalisation and its transformational impact on our society, voices have been raised globally for the importance of programming and computing for everyone. Consequently, programming has been introduced in curricula worldwide, either as part of a stand-alone computing-related subject or integrated into other subjects. While the former alternative may seem more straightforward, there are several reasons for why some countries – such as Finland – have opted for the latter approach. In this chapter, I discuss the introduction of programming in the Finnish national core curriculum for grades 1–6 (ages 7–13 years), with particular focus on the cross-curricular aspects. In addition to describing the implementation process, I present three models for introducing programming in other subjects.

StanisÅ‚aw JaÅ›kowski, in his 1948–1949 papers on propositional calculus for contradictory deductive systems, proposed discursive logic D₂. The main motivation behind D₂ is the need to properly deal with contradictions that naturally appear in many areas of philosophy and discourse. The intuitive justification of this logic reflects knowledge fusion occurring when “the theses advanced by several participants in a discourse are combined into a single system.â€� This point of view was seminal in the mid twentieth century and remains visionary nowadays.In contemporary autonomous systems operating in dynamic, unpredictable information-rich environments, distributed reasoning routinely takes place. This explains the key role of knowledge fusion, among others, in Distributed Artificial Intelligence. Therefore, different types of modern knowledge and belief bases become primarily concerned with inconsistent or lacking information. This requirement leads to recent approaches to paraconsistent and paracomplete reasoning, where nonmonotonic techniques for disambiguating inconsistencies and completing missing knowledge can be applied.In this chapter we remind JaÅ›kowski’s seminal, pioneering work on paraconsistent reasoning and indicate some of its relations to contemporary research on reasoning in Distributed AI.

<em>Dual tableaux</em> were introduced by Rasiowa and Sikorski (1960) as a cut free deduction system for classical first-order logic. In the current paper, a sound and complete proof procedure based on dual tableaux is proposed for<em> R</em>_<em>3</em>which is the standard Kleene logic augmented with a weak negation connective and an implication connective proposed, in another context, by Shepherdson (1989).<em> R₃</em>is used as a basis for defining Kleene Answer Set Programs (ASP<em>^K</em>programs). The semantics forASP<em>^K</em>programs is based on strongly supported models. Both entailment procedures and model generation procedures for normal and non-normalASP<em>^K</em>programs are proposed based on the use of dual tableaux and a model filtering technique. The dual tableau proof procedure extended with a model filtering technique is shown to be sound and complete forASP<em>^K</em>programs, both normal and non-normal. Since there is a direct relationship between answer sets for classical ASP programs and<em>R₃</em>models forASP^Kprograms, it can be shown that the sound and complete dual tableaux proof procedure with filtering for ASPK\" role=\"presentation\"&gt;ASPKprograms is also sound and complete for classical normal ASP programs. For classical non-normal ASP programs, the proof procedure is only sound, since an alternative semantics for disjunction is used inASP^K

This chapter discusses how different applications for robots will affect the labour market in the near future. Near future refers to the next 10-50 years. It is likely that several occupations will disappear, but new ones will also emerge. However, we claim that the net result will be negative, which means that we will have higher unemployment. These effects will not happen overnight, and not all occupations will be affected. But, this will happen for a sufficient amount of the population for it to become a problem for society.The observations made in this chapter are not from the point of view of a social scientist, but that of a roboticist. The observations are taken together with readings of scientific literature on automation. I do not claim to have answers to the economic and social scientific problems thrown up, but to raise a set of critical questions for the reader.All the examples in this chapter are real technologies that exist, not just in science-fiction or future technology. However, most of the examples are still in their research stage and are either not available for the general public, or still very expensive.No one can predict the future in detail, but this chapter tries to provide a scenario of the future of different kinds of occupations through the perspective of the field of robotics. I have been developing robots for 15 years and will use some examples that I have constructed, but also examples from other roboticists. The chapter does not discuss the risks of automation for all occupations, but instead focuses on blue-collar workers, such as machine operators, the transportation sector with the advent of driverless cars, white-collar workers in offices, skilled professions in the legal and medical spheres, and creative workers.

This book is in celebration of Rineke Verbrugge's 50th birthday. It is a product of an incredible effort on the part of Rineke's teachers, colleagues, students and friends who have all been won over by her ever-encouraging and positive presence in academia and also in daily life. Pertaining to Rineke's research interests, the book features eight articles on a wide range of topics - from theories of arithmetic to a study on autism. The papers on hybrid logic, formal theories of belief, probability, goals, social networks, and bisimulations enrich the logic section of the book while papers on cognitive strategizing and social cognition bring up the cognitive perspective. The themes themselves provide a compelling perception of the vast expanse of Rineke's academic interests and endeavours. A series of personal comments, stories, anecdotes, and pictures constitute the latter part of the book, adding a distinct personal touch to this volume.

Answer Set Programming is a widely known knowledge representation framework based on the logic programming paradigm that has been extensively studied in the past decades. The semantic framework for Answer Set Programs is based on the use of stable model semantics. There are two characteristics intrinsically associated with the construction of stable models for answer set programs. Any member of an answer set is supported through facts and chains of rules and those members are in the answer set only if generated minimally in such a manner. These two characteristics, supportedness and minimality, provide the essence of stable models. Additionally, answer sets are implicitly partial and that partiality provides epistemic overtones to the interpretation of disjunctiver ules and default negation. This paper is intended to shed light on these characteristics by defining a semantic framework for answer set programming based on an extended first-order Kleene logic with weak and strong negation. Additionally, a definition of strongly supported models is introduced, separate from the minimality assumption explicit in stable models. This is used to both clarify and generate alternative semantic interpretations for answer set programs with disjunctive rules in addition to answer set programs with constraint rules. An algorithm is provided for computing supported models and comparative complexity results between strongly supported and stable model generation are provided.

This chapter presents a distributed architecture for unmanned aircraft systems that provides full integration of both low autonomy and high autonomy. The architecture has been instantiated and used in a rotorbased aerial vehicle, but is not limited to use in particular aircraft systems. Various generic functionalities essential to the integration of both low autonomy and high autonomy in a single system are isolated and described. The architecture has also been extended for use with multi-platform systems. The chapter covers the full spectrum of functionalities required for operation in missions requiring high autonomy. A control kernel is presented with diverse flight modes integrated with a navigation subsystem. Specific interfaces and languages are introduced which provide seamless transition between deliberative and reactive capability and reactive and control capability. Hierarchical Concurrent State Machines are introduced as a real-time mechanism for specifying and executing low-level reactive control. Task Specification Trees are introduced as both a declarative and procedural mechanism for specification of high-level tasks. Task planners and motion planners are described which are tightly integrated into the architecture. Generic middleware capability for specifying data and knowledge flow within the architecture based on a stream abstraction is also described. The use of temporal logic is prevalent and is used both as a specification language and as an integral part of an execution monitoring mechanism. Emphasis is placed on the robust integration and interaction between these diverse functionalities using a principled architectural framework. The architecture has been empirically tested in several complex missions, some of which are described in the chapter.

A novel formalization of beliefs in multiagent systems has recently been proposed by Dunin-Kęplicz and Szałas. The aim has been to bridge the gap between idealized logical approaches to modeling beliefs and their actual implementations. Therefore the stages of belief acquisition, intermediate reasoning and final belief formation have been isolated and analyzed. In conclusion, a novel semantics reflecting those stages has been provided. This semantics is based on the new concept of epistemic profile, reflecting agent’s reasoning capabilities in a dynamic and unpredictable environment. The presented approach appears suitable for building complex belief structures in the context of incomplete and/or inconsistent information. One of original ideas is that of epistemic profiles serving as a tool for transforming preliminary beliefs into final ones. As epistemic profile can be devised both on an individual and a group level in analogical manner, a uniform treatment of single agent and group beliefs has been achieved.In the current paper these concepts are further elaborated. Importantly, we indicate an implementation framework ensuring tractability of reasoning about beliefs, propose the underlying methodology and illustrate it on an example.

This book is dedicated to the memory of Professor Zdzis{\l}aw Pawlak who passed away almost six year ago. He is the founder of the Polish school of Artificial Intelligence and one of the pioneers in Computer Engineering and Computer Science with worldwide influence. He was a truly great scientist, researcher, teacher and a human being.This book prepared in two volumes contains more than 50 chapters. This demonstrates that the scientific approaches discovered by of Professor Zdzis{\l}aw Pawlak, especially the rough set approach as a tool for dealing with imperfect knowledge, are vivid and intensively explored by many researchers in many places throughout the world. The submitted papers prove that interest in rough set research is growing and is possible to see many new excellent results both on theoretical foundations and applications of rough sets alone or in combination with other approaches.We are proud to offer the readers this book.

Research with collaborative robotic systems has much to gain by leveraging concepts and ideas from the areas of multi-agent systems and the social sciences. In this paper we propose an approach to formalizing and grounding important aspects of collaboration in a collaborative system shell for robotic systems. This is done primarily in terms of the concept of delegation, where delegation will be instantiated as a speech act. The formal characterization of the delegation speech act is based on a preformal theory of delegation proposed by Falcone and Castelfranchi. We show how the delegation speech act can in fact be used to formally ground an abstract characterization of delegation into a FIPA-compliant implementation in an agent-oriented language such as JADE, as part of a collaborative system shell for robotic systems. The collaborative system shell has been developed as a prototype and used in collaborative missions with multiple unmanned aerial vehicle systems.

The LNCS journal Transactions on Computational Collective Intelligence (TCCI) focuses on all facets of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems.This, the sixth issue of Transactions on Computational Collective Intelligence contains 10 selected papers, focusing on the topics of classification, agent cooperation, paraconsistent reasoning and agent distributed mobile interaction.

Edited in collaboration with FoLLI, the Association of Logic, Language and Information, this book collects a set of chapters of the multi-disciplinary project \"Games, actions and Social software\" which was carried out at the Netherlands Institute for Advanced Study in the Humanities and Social Sciences (NIAS) in Wassenaar, from September 2006 through January 2007.&lt;br&gt;The chapters focus on social software and the social sciences, knowledge, belief and action, perception, communication, and cooperation.

Collaborative robotic systems have much to gain by leveraging results from the area of multi-agent systems and in particular agent-oriented software engineering. Agent-oriented software engineering has much to gain by using collaborative robotic systems as a testbed. In this article, we propose and specify a formally grounded generic collaborative system shell for robotic systems and human operated ground control systems. Collaboration is formalized in terms of the concept of delegation and delegation is instantiated as a speech act. Task Specification Trees are introduced as both a formal and pragmatic characterization of tasks and tasks are recursively delegated through a delegation process implemented in the collaborative system shell. The delegation speech act is formally grounded in the implementation using Task Specification Trees, task allocation via auctions and distributed constraint problem solving. The system is implemented as a prototype on Unmanned Aerial Vehicle systems and a case study targeting emergency service applications is presented.

The study of frameworks and formalisms for reasoning about action and change [67, 58, 61, 65, 70, 3, 57] has been central to the knowledge representation field almost from the inception of Artificial Intelligence as a general field of research [52, 56]. The phrase “Temporal Action Logics� represents a class of logics for reasoning about action and change that evolved from Sandewall’s book on Features and Fluents [61] and owes much to this ambitious project. There are essentially three major parts to Sandewall’s work. He first developed a narrative-based logical framework for specifying agent behavior in terms of action scenarios. The logical framework is state-based and uses explicit time structures. He then developed a formal framework for assessing the correctness (soundness and completeness) of logics for reasoning about action and change relative to a set of well-defined intended conclusions, where reasoning problems were classified according to their ontological or epistemological characteristics. Finally, he proposed a number of logics defined semantically in terms of definitions of preferential entailment1 and assessed their correctness using his assessment framework.

Fuzzy logics are one of the most frequent approaches to model uncertainty and vagueness. In the case of fuzzy modeling, degrees of belief and disbelief sum up to 1, which causes problems in modeling the lack of knowledge and inconsistency. Therefore, so called paraconsistent intuitionistic fuzzy sets have been introduced, where the degrees of belief and disbelief are not required to sum up to 1. The situation when this sum is smaller than 1 reflects the lack of knowledge and its value greater than 1 models inconsistency. In many applications there is a strong need to guide and interpret fuzzy-like reasoning using qualitative approaches. To achieve this goal in the presence of uncertainty, lack of knowledge and inconsistency, we provide a framework for qualitative interpretation of the results of fuzzy-like reasoning by labeling numbers with words, like <em>true, false, inconsistent, unknown</em>, reflecting truth values of a suitable, usually finitely valued logical formalism.

Gilles Kahn was one of the most influential figures in the development of computer science and information technology, not only in Europe but throughout the world. This volume of articles by several leading computer scientists serves as a fitting memorial to Kahn's achievements and reflects the broad range of subjects to which he contributed through his scientific research and his work at INRIA, the French National Institute for Research in Computer Science and Control. The editors also reflect upon the future of computing: how it will develop as a subject in itself and how it will affect other disciplines, from biology and medical informatics, to web and networks in general. Its breadth of coverage, topicality, originality and depth of contribution, make this book a stimulating read for all those interested in the future development of information technology.

Welcome to the latest volume of AI Game Programming Wisdom! AI Game Programming Wisdom 4 includes a collection of more than 50 new articles featuring cutting-edge techniques, algorithms, and architectures written by industry professionals for use in commercial game development. Organized into 7 sections, this comprehensive volume explores every important aspect of AI programming to help you develop and expand your own personal AI toolbox. You'll find ready-to-use ideas, algorithms, and code in all key AI areas including general wisdom, scripting and dialogue, movement and pathfinding, architecture, tactics and planning, genre specific, and learning and adaptation. New to this volume are articles on recent advances in realistic agent, squad, and vehicle movement, as well as dynamically changing terrain, as exemplified in such popular games as Company of Heroes.You'll also find information on planning as a key game architecture, as well as important new advances in learning algorithms and player modeling. AI Game Programming Wisdom 4 features coverage of multiprocessor architectures, Bayesian networks, planning architectures, conversational AI, reinforcement learning, and player modeling.These valuable and innovative insights and issues offer the possibility of new game AI experiences and will undoubtedly contribute to taking the games of tomorrow to the next level.

Annotation The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. Volume VI of the Transactions on Rough Sets (TRS) commemorates the life and work of Zdzislaw Pawlak (1926-2006). His legacy is rich and varied. Prof. Pawlak's research contributions have had far-reaching implications inasmuch as his works are fundamental in establishing new perspectives for scientific research in a wide spectrum of fields. This volume of the TRS presents papers that reflect the profound influence of a number of research initiatives by Professor Pawlak. In particular, this volume introduces a number of new advances in the foundations and applications of artificial intelligence, engineering, logic, mathematics, and science. These advances have significant implications in a number of research areas such as the foundations of rough sets, approximate reasoning, bioinformatics, computational intelligence, cognitive science, data mining, information systems, intelligent systems, machine intelligence, and security.

The present book is a festschrift in honor of Luigia Carlucci Aiello. The 18 articles included are written by former students, friends, and international colleagues, who have cooperated with Luigia Carlucci Aiello, scientifically or in AI boards or committees. The contributions by reputed researchers span a wide range of AI topics and reflect the breadth and depth of Aiello's own work

Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g., in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, and genetic algorithms.It is well understood now in the soft computing community that hybrid approaches combining various paradigms provide very promising attempts to solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neurocomputing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g., in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, and genetic algorithms.It is well understood now in the soft computing community that hybrid approaches combining various paradigms provide very promising attempts to solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neurocomputing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

This last volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems is - together with Volume 6 - devoted to the topics Reasoning and Dynamics, covering both the topics of \"Dynamics of Reasoning,\" where reasoning is viewed as a process, and \"Reasoning about Dynamics,\" which must be understood as pertaining to how both designers of, and agents within dynamic systems may reason about these systems. The present volume presents work done in this context and is more focused on \"reasoning about dynamics,\" viz. how (human and artificial) agents reason about (systems in) dynamic environments in order to control them. In particular modelling frameworks and generic agent models for modelling these dynamic systems and formal approaches to these systems such as logics for agents and formal means to reason about agent-based and compositional systems, and action &amp; change more in general are considered.

Developing agents for simulation environments is usually the responsibility of computer experts. However, as domain experts have superior knowledge of the intended agent behavior, it is desirable to have domain experts directly specifying behavior. In this paper we describe a system which allows non-computer experts to specify the behavior of agents for the RoboCup domain. An agent designer is presented with a Graphical User Interface with which he can specify behaviors and activation conditions for behaviors in a layered behavior-based system. To support the testing and debugging process we are also developing interfaces that show, in real-time, the world from the agents perspective and the state of its reasoning process.

In this paper we present an AI programming organised around the RoboCup soccer simulation system. The course participants create a number of software agents that form a team, and participate in a tournament at the end of the course. The use of a challenging and interesting task, and the incentive of having a tournament has made the course quite successful, both in term of enthusiasm of the students and of knowledge acquired. In the paper we describe the structure of the course, discuss in what respect we think the course has met its aim, and the opinions of the students about the course.

Sandewall has recently proposed a systematic approach to the representation of knowledge about dynamical systems that includes a general framework in which to assess the range of applicability of existing and new logics for action and change and to provide a means of studying whether and in what sense the logics of action and change are relevant for intelligent agents. As part of the framework, a number of logics of preferential entailment are introduced and assessed for particular classes of action scenario descriptions. This paper provides syntactic characterizations of several of these relations of preferential entailment in terms of standard FOPC and circumscription axioms. The intent is to simplify the process of comparison with existing formalisms which use more traditional techniques and to provide a basis for studying the feasibility of compiling particular classes of problems into logic programs.