Recent Advances in General Game Playing

The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. GGP research attempts to design systems that work well across different game types, including unknown new games. In this review, we present a survey of recent advances (2011 to 2014) in GGP for both traditional games and video games. It is notable that research on GGP has been expanding into modern video games. Monte-Carlo Tree Search and its enhancements have been the most influential techniques in GGP for both research domains. Additionally, international competitions have become important events that promote and increase GGP research. Recently, a video GGP competition was launched. In this survey, we review recent progress in the most challenging research areas of Artificial Intelligence (AI) related to universal game playing

An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

SEPEC conference proceedings: Hypermedia and Information Reconstruction. Aerospace applications and research directions. Addendum

The papers presented at the conference on hypermedia and information reconstruction are compiled. The following subject areas are covered: hypertext, typographic man, and the notion of literacy; a knowledge base browser using hypermedia; Ai GERM - a logic programming front end for GERM; and HEAVENS system for software artifacts

Analysable software language translations

Dissertação para obtenção do Grau de Doutor em Engenharia InformáticaThe most difficult tasks in the Software Language Engineering (SLE) process, are the design of the semantics of a Domain Specific Modeling Language (DSML), its implementation (typically in a form of a compiler), and also its verification and validation. On the one hand, the choice of the appropriate level of abstraction when designing a DSML’s semantics, affects directly its usability, and the potential for its analysis. On the other hand, in practice, not only the compiler’s implementation, but also its verification and validation are performed manually, while having as reference the DSML’s semantic models. The challenge of this research work is to apply a complete model driven software development approach in the tasks of designing a DSML’s semantics, implementing, verifying and validating DSMLs’ compilers. This involves the choice of the most appropriate abstraction levels, and the design and development of adequate tools to support SLE practitioners on these tasks. This thesis reports: i) the design and implementation of formal languages (and associated tools) to support the task of DSML’s semantics design (i.e., DSLTrans and SOS); ii) the automatic generation of DSMLs’ compilers based on translation specifications; and iii) automated validation of DSMLs’ semantic designs based on the analysis of translation specifications. Finally, the approach presented in this thesis is illustrated with the design and implementation of a real life DSML

OpenCog Hyperon: A Framework for AGI at the Human Level and Beyond

An introduction to the OpenCog Hyperon framework for Artificiai General Intelligence is presented. Hyperon is a new, mostly from-the-ground-up rewrite/redesign of the OpenCog AGI framework, based on similar conceptual and cognitive principles to the previous OpenCog version, but incorporating a variety of new ideas at the mathematical, software architecture and AI-algorithm level. This review lightly summarizes: 1) some of the history behind OpenCog and Hyperon, 2) the core structures and processes underlying Hyperon as a software system, 3) the integration of this software system with the SingularityNET ecosystem's decentralized infrastructure, 4) the cognitive model(s) being experimentally pursued within Hyperon on the hopeful path to advanced AGI, 5) the prospects seen for advanced aspects like reflective self-modification and self-improvement of the codebase, 6) the tentative development roadmap and various challenges expected to be faced, 7) the thinking of the Hyperon team regarding how to guide this sort of work in a beneficial direction ... and gives links and references for readers who wish to delve further into any of these aspects

A Survey of Knowledge Representation in Service Robotics

Within the realm of service robotics, researchers have placed a great amount of effort into learning, understanding, and representing motions as manipulations for task execution by robots. The task of robot learning and problem-solving is very broad, as it integrates a variety of tasks such as object detection, activity recognition, task/motion planning, localization, knowledge representation and retrieval, and the intertwining of perception/vision and machine learning techniques. In this paper, we solely focus on knowledge representations and notably how knowledge is typically gathered, represented, and reproduced to solve problems as done by researchers in the past decades. In accordance with the definition of knowledge representations, we discuss the key distinction between such representations and useful learning models that have extensively been introduced and studied in recent years, such as machine learning, deep learning, probabilistic modelling, and semantic graphical structures. Along with an overview of such tools, we discuss the problems which have existed in robot learning and how they have been built and used as solutions, technologies or developments (if any) which have contributed to solving them. Finally, we discuss key principles that should be considered when designing an effective knowledge representation.Comment: Accepted for RAS Special Issue on Semantic Policy and Action Representations for Autonomous Robots - 22 Page