Vision Science and Technology at NASA: Results of a Workshop

A broad review is given of vision science and technology within NASA. The subject is defined and its applications in both NASA and the nation at large are noted. A survey of current NASA efforts is given, noting strengths and weaknesses of the NASA program

Computationally Efficient Relational Reinforcement Learning

Relational Reinforcement Learning (RRL) is a technique that enables Reinforcement Learning (RL) agents to generalize from their experience, allowing them to learn over large or potentially infinite state spaces, to learn context sensitive behaviors, and to learn to solve variable goals and to transfer knowledge between similar situations. Prior RRL architectures are not sufficiently computationally efficient to see use outside of small, niche roles within larger Artificial Intelligence (AI) architectures. I present a novel online, incremental RRL architecture and an implementation that is orders of magnitude faster than its predecessors. The first aspect of this architecture that I explore is a computationally efficient implementation of an adaptive Hierarchical Tile Coding (aHTC), a kind of Adaptive Tile Coding (ATC) in which more general tiles which cover larger portions of the state-action space are kept as ones that cover smaller portions of the state-action space are introduced, using k-dimensional tries (k-d tries) to implement the value function for non-relational Temporal Difference (TD) methods. In order to achieve comparable performance for RRL, I implement the Rete algorithm to replace my k-d tries due to its efficient handling of both the variable binding problem and variable numbers of actions. Tying aHTCs and Rete together, I present a rule grammar that both maps aHTCs onto Rete and allows the architecture to automatically extract relational features in order to support adaptation of the value function over time. I experiment with several refinement criteria and additional functionality with which my agents attempt to determine if rerefinement using different features might allow them to better learn a near optimal policy. I present optimal results using a value criterion for several variants of BlocksWorld. I provide transfer results for BlocksWorld and a scalable Taxicab domain. I additionally introduce a Higher Order Grammar (HOG) that grants online, incremental RRL agents additional flexibility to introduce additional variables and corresponding relations as needed in order to learn effective value functions. I evaluate agents that use the HOG on a version of Blocks World and on an Adventure task. In summary, I present a new online, incremental RRL architecture, a grammar to map aHTCs onto the Rete, and an implementation that is orders of magnitude faster than its predecessors.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145859/1/bazald_1.pd

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

Design and Code Optimization for Systems with Next-generation Racetrack Memories

With the rise of computationally expensive application domains such as machine learning, genomics, and fluids simulation, the quest for performance and energy-efficient computing has gained unprecedented momentum. The significant increase in computing and memory devices in modern systems has resulted in an unsustainable surge in energy consumption, a substantial portion of which is attributed to the memory system. The scaling of conventional memory technologies and their suitability for the next-generation system is also questionable. This has led to the emergence and rise of nonvolatile memory ( NVM ) technologies. Today, in different development stages, several NVM technologies are competing for their rapid access to the market. Racetrack memory ( RTM ) is one such nonvolatile memory technology that promises SRAM -comparable latency, reduced energy consumption, and unprecedented density compared to other technologies. However, racetrack memory ( RTM ) is sequential in nature, i.e., data in an RTM cell needs to be shifted to an access port before it can be accessed. These shift operations incur performance and energy penalties. An ideal RTM , requiring at most one shift per access, can easily outperform SRAM . However, in the worst-cast shifting scenario, RTM can be an order of magnitude slower than SRAM . This thesis presents an overview of the RTM device physics, its evolution, strengths and challenges, and its application in the memory subsystem. We develop tools that allow the programmability and modeling of RTM -based systems. For shifts minimization, we propose a set of techniques including optimal, near-optimal, and evolutionary algorithms for efficient scalar and instruction placement in RTMs . For array accesses, we explore schedule and layout transformations that eliminate the longer overhead shifts in RTMs . We present an automatic compilation framework that analyzes static control flow programs and transforms the loop traversal order and memory layout to maximize accesses to consecutive RTM locations and minimize shifts. We develop a simulation framework called RTSim that models various RTM parameters and enables accurate architectural level simulation. Finally, to demonstrate the RTM potential in non-Von-Neumann in-memory computing paradigms, we exploit its device attributes to implement logic and arithmetic operations. As a concrete use-case, we implement an entire hyperdimensional computing framework in RTM to accelerate the language recognition problem. Our evaluation shows considerable performance and energy improvements compared to conventional Von-Neumann models and state-of-the-art accelerators

Tekes projekti SuperMachines loppuraportti

Tutkimuksessa kerättiin best practice aineistoa ja kehitettiin internet alusta kerätyn aineiston tutkimiseen ja hakujen suorittamiseen. Aineisto löytyy internet osoitteesta: http://www.amcase.info/. Rekisteröitymällä kuka vain voi syöttää alustalle lisää aineistoa. Kappaleiden suunnitteluohjeet on julkaistu Suomen pikavalmistusyhdistyksen sivuilla: http://firpa.fi/html/am-tietoa.html. Ohjeesta löytyy mm. suositeltu minimi seinämänvahvuus, suositellun pienimmän yksityiskohdan koko, tyypillinen markkinoilta löytyvä rakennuskammin koko, sekä tyypilliset materiaalit. Valmiiden kokoonpanojen ja mekanismien suunnitteluun muodostettiin Objet 30 ja UPrint SE+ laitteelle ohjeistus josta löytyy pienin radiaalinen välys, aksiaalinen välys, sekä pienin rako riippuen rakennussuunnasta. Tutkimusprojektin aikana seurattiin alan teknologian kehitystä. Kahden vuoden aikana markkinoille ilmaantui noin. 50 uutta laitevalmistajaa, sekä noin 300 erilaista laitetta, sekä lukuisia materiaaleja. Merkittävimmät uudistukset listattiin ja pohdittiin mahdollisia kehityssuuntia. Kaikki uudet toimijat ja laitteet päivitettiin Firpan ylläpitämään tietokantaan: http://firpa.fi/html/am-tietoa.html. Markkinoilla on selvä suuntaus tuotantokomponenttien valmistamiseen, kotitulostimien hintojen laskemiseen, sekä isompien kappaleiden valmistamiseen. Muovilevy komponenttien muovaamista tutkittiin laserin ja alipaineen avulla DDShape laitteella. Laitteella onnistuttiin tekemään testikappaleita ja laitetta saatiin kehitettyä eteenpäin. Laitteiston kehittämiseksi ja kaupallistamisen tueksi Tekes on myöntänyt "Tutkimusideoista uutta tietoa ja liiketoimintaa" (TUTLI) rahoituksen. ISF mini projektissa onnistuttiin kehittämään edullinen pienten kappaleiden painomuovauskone. Samalla kartoitettiin laitteelle soveltuvat parametrit ja rajoitukset. Laseravusteisella muovaamisella päästään kuparilla isompaan seinämän kaltevuuteen ja pinnalaatu pysyy hyvänä. Teräksellä laserista ei ollut juuri hyötyä ja alumiinilla muovattavuus kyllä parani, mutta pinnalaatu huononi. AM kappaleiden viimeistelykoneistuksessa tutkittiin muovisten kappaleiden viimeistely jyrsimällä, sekä metallikappaleiden automaattista hiontaa. Jyrsinnässä vertailtiin eri menetelmillä tehtyjä kappaleita, sekä mitattiin kappaleiden mittatarkkuutta ja geometrisia toleransseja. Huonosta kotitulostimella tehdystä kappaleesta on vaikea saada hyvää kappaletta vaikka se viimeisteltäisiin koneistamalla. Suurimmat ongelmat liittyvät kappaleiden vääntymiseen johtuen lämpöjännityksistä valmistusprosessin aikana. Kappaleiden automaattisessa hionnassa parhaat tulokset saatiin DMLS kappaleille käyttämällä hionta-aineena teräshauleja ja pyörittämällä niitä hiottavat kappaleen kanssa rummussa. Ra arvo parani tällöin noin seitsemästä mikrometristä kolmeen mikrometriin

One Model to Rule them all: Multitask and Multilingual Modelling for Lexical Analysis

When learning a new skill, you take advantage of your preexisting skills and knowledge. For instance, if you are a skilled violinist, you will likely have an easier time learning to play cello. Similarly, when learning a new language you take advantage of the languages you already speak. For instance, if your native language is Norwegian and you decide to learn Dutch, the lexical overlap between these two languages will likely benefit your rate of language acquisition. This thesis deals with the intersection of learning multiple tasks and learning multiple languages in the context of Natural Language Processing (NLP), which can be defined as the study of computational processing of human language. Although these two types of learning may seem different on the surface, we will see that they share many similarities. The traditional approach in NLP is to consider a single task for a single language at a time. However, recent advances allow for broadening this approach, by considering data for multiple tasks and languages simultaneously. This is an important approach to explore further as the key to improving the reliability of NLP, especially for low-resource languages, is to take advantage of all relevant data whenever possible. In doing so, the hope is that in the long term, low-resource languages can benefit from the advances made in NLP which are currently to a large extent reserved for high-resource languages. This, in turn, may then have positive consequences for, e.g., language preservation, as speakers of minority languages will have a lower degree of pressure to using high-resource languages. In the short term, answering the specific research questions posed should be of use to NLP researchers working towards the same goal.Comment: PhD thesis, University of Groninge

Effect of different distance measures in result of cluster analysis

The objective of this master’s thesis was to explore different distance measures that could be used in clustering and to evaluate how different distance measures in K-medoid clustering method would affect the clustering output. The different distance measures used in this research includes Euclidean, Squared Euclidean, Manhattan, Chebyshev and Mahalanobis distance. To achieve the research objective, K-medoid method with different distance measures was applied to a spatial dataset to explore relative information revealed by each distance measure. The effect of each distance measure on output is documented and the output was further compared with each other to reveal the differences between each distance measure. The study starts with literature review of cluster analysis process where necessary steps for performing cluster analysis are explained. In literature section, different clustering methods with particular characteristics of each method are described that would serve as basis for choice of clustering method. Data description and data analysis is included thereafter which is followed by interpretation of clustering result and its use for Terrain analysis. Terrain analysis has its significance in forest industry, military as well as crisis management and is usually concerned with off-road mobility of a vehicle or a group of vehicles between given locations. In case of terrain analysis, clustering could be used to group the similar areas and determine the off-road mobility of a particular vehicle. This result could be further categorized according to suitability of the item in the cluster and interpreted using expert evaluation in order to reveal useful information about mobility in a terrain. Cluster Validation measures were applied to output of clustering to determine the differences between different distance measures. The findings of this study indicate that in the study area, there exists some level of differences in the result of clustering when different distance measures are used. This difference is then interpreted with the help of input dataset and expert opinion to understand the effect of different distance measures in the dataset. Finally, the study provides basis for mobility analysis with help of clustering output

Innovation of product modularity development through the integration of a formal Industrial Design framework

Growing numbers of global manufacturers are not only adopting the modularity concept, but integrating design methodologies that explicitly focused on achieving a range of competitive advantages through the enhancement of product appearance and utilities designs. The rising interest in industrial design is also an interesting symptom of changes in the approach to new product development, hence, integrating industrial design in modular product design posed a new challenge. In meeting these challenges, a formal Industrial Design framework known as InDFM (Industrial Design Framework for Modular Product Design/Development) was developed to support the innovation of design in modular product development. Within the InDFM, a methodology is developed for modular product design realisation. This research embarked with identifying the appropriate range of product as the focus of the investigation, followed by qualitative surveys on the design and development processes relevant to the selected product. The surveys were conducted in modular product companies within a range of industries related to the product, in the U.K., Belgium and Malaysia. Literatures reviews were also conducted on related domains across a range of application to understand the fundamentals of modularity and industrial design processes that are relevant to the domains. Data findings from these exercises were used to identify InDFM construction components, which were also vital to develop a technical standard for implementation of the InDFM. To evaluate its practicability, the InDFM was retrospectively applied in an existing modular product design process of a selected company. The evaluation focused on process compatibility of industrial design and modular design processes. Validation of the process compatibility emphasised the quality of integration at all stages of the design and development process. In conclusion, industrial design applications in a highly technical process of modular product design provide a design-driven innovation to complement the engineering driven innovation in the process. The combinations were proven to enhance the visual, interactive, and the feasibility contents of a modular product apart from providing a broader perspective to the objective of product modularity. InDFM also provides design practitioners with systematic design methodology to integrate both processes, thus performed as a tool for innovation that facilitate the revision of object identity, break away from the existing design rules and generating new rules. Additionally, as InDFM is a flexible methodology, innovation of modular product design through industrial design is accessible to any product company, small scale or big organisation that would want to acquire an advanced interactive version of the InDFM in the future