Object-Oriented Dynamics Learning through Multi-Level Abstraction

Object-based approaches for learning action-conditioned dynamics has demonstrated promise for generalization and interpretability. However, existing approaches suffer from structural limitations and optimization difficulties for common environments with multiple dynamic objects. In this paper, we present a novel self-supervised learning framework, called Multi-level Abstraction Object-oriented Predictor (MAOP), which employs a three-level learning architecture that enables efficient object-based dynamics learning from raw visual observations. We also design a spatial-temporal relational reasoning mechanism for MAOP to support instance-level dynamics learning and handle partial observability. Our results show that MAOP significantly outperforms previous methods in terms of sample efficiency and generalization over novel environments for learning environment models. We also demonstrate that learned dynamics models enable efficient planning in unseen environments, comparable to true environment models. In addition, MAOP learns semantically and visually interpretable disentangled representations.Comment: Accepted to the Thirthy-Fourth AAAI Conference On Artificial Intelligence (AAAI), 202

Common Territory? : Comparing the IMP Approach with Economic Geography

The IMP research tradition has always been open to the cross-fertilisation of ideas with other social science disciplines that study similar phenomena. Recent years have seen a growing interest among IMP researchers in phenomena such as regional strategic networks, spatial clusters and innovation and new business development in networks. IMP papers published on these topics are increasingly citing conceptual frameworks and empirical findings from the field of economic geography. This paper discusses the development of IMP thought and the development of thought in economic geography (particularly evolutionary economic geography), and compares their approaches to the analysis of regional phenomena. The goal is to identify key ideas from economic geography that have been under-exploited in IMP research, in order to suggest original new approaches available to IMP researchers interested in these fields. A number of such ideas are explored: proximity as a multi-dimensional and multi-faceted concept; the distinction between, and relative importance of, learning activities arising automatically from being embedded in a community (local or regional buzz) and learning activities arising from positive investment in channels of communication (pipelines); the concept of relational capital developed by economic geographers; and, conceptualisations of externalities commonly used in the study of spatial clustersPeer reviewedFinal Accepted Versio

Some Requests for Machine Learning Research from the East African Tech Scene

Based on 46 in-depth interviews with scientists, engineers, and CEOs, this document presents a list of concrete machine research problems, progress on which would directly benefit tech ventures in East Africa.Comment: Presented at NIPS 2018 Workshop on Machine Learning for the Developing Worl

A network-based view of regional growth

The need to better understand the mechanisms underlying regional growth patterns is widely recognised. This paper argues that regional growth is partly a function of the value created through inter-organisational flows of knowledge within and across regions. It is proposed that investment in calculative networks by organisations to access knowledge is a form of capital, termed network capital, which should be incorporated into regional growth models. The paper seeks to develop a framework to capture the value of network capital within these models based on the spatial configuration and the nature of the knowledge flowing through networks

Regional Learning Networks in Medium-Tech Technologies and European Integration

The paper aims at investigating the transfer of tacit knowledge both at the regional and at the interregional level and it focuses on the factors and forms of the processes of interactive learning between small and medium size in medium technology sectors. The analysis proceeds from the contributions of four strands of literature, focusing on economics of agglomeration, cognitive economics, industrial strategic alliances and governance in a knowledge economy. While industrial economics interprets technology spill-over at the local level as an automatic and chaotic process allowed by geographical proximity of the firms, regional economics identifies different specific types of flows and networks, which link together in an organized way the various firms and other private and public actors within a given regional innovation system. Cognitive economics may bring a significant contribution, as it considers the relevance for economics of human cognitive aspects and it discovers the key role in the creation of new ideas of selected factors, such as the stimulus by changes in the external environment, the process of “neurognosis†or negative reaction aiming to the protection of the internal integrity, the search process constrained by cognitive proximity, the success in pattern making and the achievement of consistency and compatability, the process of “exaptation†or reconversion leading to path-dependency, the creation of new connections and routines and institutions, which allows to save the limited cognitive capacity of individuals and organizations. This theoretical framework in the analysis of the processes of knowledge creation may be schematically represented through the model of “Territorial Knowledge Managementâ€, which aims at promoting the interactive learning processes within the regional innovation systems and focuses on a selected list of knowledge levers, such as: market orientation, accessibility, receptiveness, common identity, creativity and governance. On the base of these theoretical concepts and tools, the paper analyses various case studies of firms embedded in different industrial clusters in Europe, focusing on the forms of the process of interactive learning and innovation between the various regional actors. Finally, the paper attempts to derive from that analysis useful indications for the possible extension of knowledge and innovation networks at the interregional and international level and for decreasing the regional divide in a modern knowledge economy. The research has been undertaken within the framework of the project: “IKINET – International Knowledge and Innovation Network†(EU FP6, N° CIT2-CT-2004-506242). Keywords: knowledge creation, interactive learning processes, industrial clusters, innovation policies, European integration, medium technology sectors, small and medium size firms.

Local Nodes in Global Networks: The Geography of Knowledge Flows in Biotechnology Innovation

The literature on innovation and interactive learning has tended to emphasize the importance of local networks, inter-firm collaboration and knowledge flows as the principal source of technological dynamism. More recently, however, this view has come to be challenged by other perspectives that argue for the importance of non-local knowledge flows. According to this alternative approach, truly dynamic economic regions are characterized both by dense local social interaction and knowledge circulation, as well as strong inter-regional and international connections to outside knowledge sources and partners. This paper offers an empirical examination of these issues by examining the geography of knowledge flows associated with innovation in biotechnology. We begin by reviewing the growing literature on the nature and geography of innovation in biotechnology research and the commercialization process. Then, focusing on the Canadian biotech industry, we examine the determinants of innovation (measured through patenting activity), paying particular attention to internal resources and capabilities of the firm, as well as local and global flows of knowledge and capital. Our study is based on the analysis of Statistics Canada’s 1999 Survey of Biotechnology Use and Development, which covers 358 core biotechnology firms. Our findings highlight the importance of in-house technological capability and absorptive capacity as determinants of successful innovation in biotechnology firms. Furthermore, our results document the precise ways in which knowledge circulates, in both embodied and disembodied forms, both locally and globally. We also highlight the role of formal intellectual property transactions (domestic and international) in promoting knowledge flows. Although we document the importance of global networks in our findings, our results also reveal the value of local networks and specific forms of embedding. Local relational linkages are especially important when raising capital—and the expertise that comes with it—to support innovation. Nevertheless, our empirical results raise some troubling questions about the alleged pre-eminence of the local in fostering innovation