Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

A Review of Platforms for the Development of Agent Systems

Agent-based computing is an active field of research with the goal of building autonomous software of hardware entities. This task is often facilitated by the use of dedicated, specialized frameworks. For almost thirty years, many such agent platforms have been developed. Meanwhile, some of them have been abandoned, others continue their development and new platforms are released. This paper presents a up-to-date review of the existing agent platforms and also a historical perspective of this domain. It aims to serve as a reference point for people interested in developing agent systems. This work details the main characteristics of the included agent platforms, together with links to specific projects where they have been used. It distinguishes between the active platforms and those no longer under development or with unclear status. It also classifies the agent platforms as general purpose ones, free or commercial, and specialized ones, which can be used for particular types of applications.Comment: 40 pages, 2 figures, 9 tables, 83 reference

What is a Good Pattern of Life Model? Guidance for Simulations

We have been modeling an ever-increasing scale of applications with agents that simulate the pattern of life (PoL) and real-world human behaviors in diverse regions of the world. The goal is to support sociocultural training and analysis. To measure progress, we propose the definition of a measure of goodness for such simulated agents, and review the issues and challenges associated with first-generation (1G) agents. Then we present a second generation (2G) agent hybrid approach that seeks to improve realism in terms of emergent daily activities, social awareness, and micro-decision making in simulations. We offer a PoL case study with a mix of 1G and 2G approaches that was able to replace the pucksters and avatar operators needed in large-scale immersion exercises. We conclude by observing that a 1G PoL simulation might still be best where large-scale, pre-scripted training scenarios will suffice, while the 2G approach will be important for analysis or if it is vital to learn about adaptive opponents or unexpected or emergent effects of actions. Lessons are shared about ways to blend 1G and 2G approaches to get the best of each

Agoric computation: trust and cyber-physical systems

In the past two decades advances in miniaturisation and economies of scale have led to the emergence of billions of connected components that have provided both a spur and a blueprint for the development of smart products acting in specialised environments which are uniquely identifiable, localisable, and capable of autonomy. Adopting the computational perspective of multi-agent systems (MAS) as a technological abstraction married with the engineering perspective of cyber-physical systems (CPS) has provided fertile ground for designing, developing and deploying software applications in smart automated context such as manufacturing, power grids, avionics, healthcare and logistics, capable of being decentralised, intelligent, reconfigurable, modular, flexible, robust, adaptive and responsive. Current agent technologies are, however, ill suited for information-based environments, making it difficult to formalise and implement multiagent systems based on inherently dynamical functional concepts such as trust and reliability, which present special challenges when scaling from small to large systems of agents. To overcome such challenges, it is useful to adopt a unified approach which we term agoric computation, integrating logical, mathematical and programming concepts towards the development of agent-based solutions based on recursive, compositional principles, where smaller systems feed via directed information flows into larger hierarchical systems that define their global environment. Considering information as an integral part of the environment naturally defines a web of operations where components of a systems are wired in some way and each set of inputs and outputs are allowed to carry some value. These operations are stateless abstractions and procedures that act on some stateful cells that cumulate partial information, and it is possible to compose such abstractions into higher-level ones, using a publish-and-subscribe interaction model that keeps track of update messages between abstractions and values in the data. In this thesis we review the logical and mathematical basis of such abstractions and take steps towards the software implementation of agoric modelling as a framework for simulation and verification of the reliability of increasingly complex systems, and report on experimental results related to a few select applications, such as stigmergic interaction in mobile robotics, integrating raw data into agent perceptions, trust and trustworthiness in orchestrated open systems, computing the epistemic cost of trust when reasoning in networks of agents seeded with contradictory information, and trust models for distributed ledgers in the Internet of Things (IoT); and provide a roadmap for future developments of our research

GECA: A Global Edge Computing Architecture

[EN]The smart scenarios are in continuous advance thanks to the group of devices that are always connected to Internet. In the last 10 years this phenomenon has been called Internet of Things (IoT). The adoption of the IoT to generate these intelligent scenarios or smart has motivated that governments, universities, research centers or companies are in constant evolution to face the challenges brought by the deployment of IoT platforms. Its disruption in all environments generates large volumes of data, requirements by users for their applications to respond in real time, but with low bandwidth or power consumption, and without delays. The challenges presented by the development of applications for the IoT has occasioned the emergence of technologies such as Edge Computing. This paper presents GECA: A Global Edge Computing Architecture, an architecture based on Edge Computing, which has been deployed in smart farming and smart energy scenarios, with the aim of demonstrating that it is possible to reduce latency, energy consumption and bandwidth costs and integrate Edge computing in IoT platforms

The role of Artificial Intelligence and distributed computing in IoT applications

[EN]The exchange of ideas between scientists and technicians, from both academic and business areas, is essential in order to ease the development of systems which can meet the demands of today’s society. Technology transfer in this field is still a challenge and, for that reason, this type of contributions are notably considered in this compilation. This book brings in discussions and publications concerning the development of innovative techniques of IoT complex problems. The technical program focuses both on high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 10 chapters were submitted to this book. The editors particularly encouraged and welcomed contributions on AI and distributed computing in IoT applications.Financed by regional government of Castilla y León and FEDER funds

The role of Artificial Intelligence and Distributed computing in IoT applications

[ES] La serie «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» contiene publicaciones sobre la teoría y aplicaciones de la computación distribuida y la inteligencia artificial en el Internet de las cosas. Prácticamente todas las disciplinas como la ingeniería, las ciencias naturales, la informática y las ciencias de la información, las TIC, la economía, los negocios, el comercio electrónico, el medio ambiente, la salud y las ciencias de la vida están cubiertas. La lista de temas abarca todas las áreas de los sistemas inteligentes modernos y la informática como: inteligencia computacional, soft computing incluyendo redes neuronales, inteligencia social, inteligencia ambiental, sistemas auto-organizados y adaptativos, computación centrada en el ser humano y centrada en el ser humano, sistemas de recomendación, control inteligente, robótica y mecatrónica, incluida la colaboración entre el ser humano y la máquina, paradigmas basados en el conocimiento, paradigmas de aprendizaje, ética de la máquina, análisis inteligente de datos, gestión del conocimiento, agentes inteligentes, toma de decisiones inteligentes y apoyo, seguridad de la red inteligente, gestión de la confianza, entretenimiento interactivo, inteligencia de la Web y multimedia. Las publicaciones en el marco de «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» son principalmente las actas de seminarios, simposios y conferencias. Abarcan importantes novedades recientes en la materia, tanto de naturaleza fundacional como aplicable. Un importante rasgo característico de la serie es el corto tiempo de publicación. Esto permite una rápida y amplia difusión de los resultados de las investigaciones[EN] The series «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» contains publications on the theory and applications of distributed computing and artificial intelligence in the Internet of Things. Virtually all disciplines such as engineering, natural sciences, computer and information sciences, ICT, economics, business, e-commerce, environment, health and life sciences are covered. The list of topics covers all areas of modern intelligent systems and computer science: computational intelligence, soft computing including neural networks, social intelligence, ambient intelligence, self-organising and adaptive systems, human-centred and people-centred computing, recommendation systems, intelligent control, robotics and mechatronics including human-machine collaboration, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, web intelligence, and multimedia. The publications in the framework of «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» are mainly the proceedings of seminars, symposia and conferences. They cover important recent developments in the field, whether of a foundational or applicable character. An important feature of the series is the short publication time. This allows for the rapid and wide dissemination of research results

An Online Agent-Based Search Approach in Automated Computer Game Testing with Model Construction

The complexity of computer games is ever increasing. In this setup, guiding an automated test algorithm to find a solution to solve a testing task in a game's huge interaction space is very challenging. Having a model of a system to automatically generate test cases would have a strong impact on the effectiveness and efficiency of the algorithm. However, manually constructing a model turns out to be expensive and time-consuming. In this study, we propose an online agent-based search approach to solve common testing tasks when testing computer games that also constructs a model of the system on-the-fly based on the given task, which is then exploited to solve the task. To demonstrate the efficiency of our approach, a case study is conducted using a game called Lab Recruits