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Reinforced Structured State-Evolution for Vision-Language Navigation
[article]
2022
arXiv
pre-print
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Vision-and-language Navigation (VLN) task requires an embodied agent to navigate to a remote location following a natural language instruction. ...
In this paper, we propose a novel Structured state-Evolution (SEvol) model to effectively maintain the environment layout clues for VLN. ...
To utilise the layout information, we propose a novel model for vision-andlanguage navigation, named the Structured state-Evolution model (SEvol), which maintains a structured memory and evolves a structured ...
arXiv:2204.09280v2
fatcat:mjez4tbmafe35ljq3ttokhzbyy
A Survey on Visual Navigation for Artificial Agents with Deep Reinforcement Learning
2020
IEEE Access
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Then, we systematically describe five main categories of visual DRL navigation: direct DRL vNavigation, hierarchical DRL vNavigation, multi-task DRL vNavigation, memory-inference DRL vNavigation and vision-language ...
Visual navigation for artificial agents with deep reinforcement learning (DRL) is a new research hotspot in artificial intelligence and robotics that incorporates the decision making of DRL into visual ...
Fig. 15 shows the architecture of vision-and-language navigation, in which the fusion of language instruction and vision as state inputs are fed into artificial agents for navigation policy. ...
doi:10.1109/access.2020.3011438
fatcat:ie6qvu24qbapbjxtiudh7fumgy
NavigationNet: A Large-scale Interactive Indoor Navigation Dataset
[article]
2018
arXiv
pre-print
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To address this, we proposed NavigationNet, a computer vision dataset and benchmark to allow the utilization of deep reinforcement learning on scene-understanding-based indoor navigation. ...
We also proposed and formalized several typical indoor routing problems that are suitable for deep reinforcement learning. ...
NavigationNet NavigationNet is specifically designed for applying reinforcement learning methods to indoor navigation tasks. ...
arXiv:1808.08374v1
fatcat:25kouetf7jcp7msmrhczqjerzi
VisualHints: A Visual-Lingual Environment for Multimodal Reinforcement Learning
[article]
2020
arXiv
pre-print
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We present VisualHints, a novel environment for multimodal reinforcement learning (RL) involving text-based interactions along with visual hints (obtained from the environment). ...
However, most traditional RL environments either solve pure vision-based tasks like Atari games or video-based robotic manipulation; or entirely use natural language as a mode of interaction, like Text-based ...
LSTM-DQN assumed some structure in the output command setting; this was tackled by DRRN (Deep Reinforcement Relevance Network) by addressing a natural language action space for generating action commands ...
arXiv:2010.13839v1
fatcat:rtwpdbflvzcyln4ndeaa4aqv5m
Navigating Borders: The Evolution of the Cass Clay Food Partners
2018
Journal of Agriculture, Food Systems, and Community Development
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We also highlight the many types of boundaries the network has navigated in order to attain success in advancing alternative food systems for the Red River Valley community. ...
In this paper, we describe the evolution of the network from project-based work to policy development to a partnership that integrates both programs and policy for greater impact. ...
Acknowledgments The authors would like to thank the Cass Clay Food Partners steering committee and the Cass Clay Food Commission for their work to increase food access and build a health food system across ...
doi:10.5304/jafscd.2018.08b.010
fatcat:sttvrcw2nvchzclfibokhp4nce
Enhancing a requirements baseline with scenarios
1997
Requirements Engineering
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For us, a scenario is an evolving description of situations in the environment. ...
Our proposal is framed by Leite's work on a client-oriented requirements baseline, which aims to model the external requirements of a software system and its evolution. ...
Our proposal is 197 innovative in three important aspects: the use of scenarios as means for describing evolution, the vision that scenarios start from situations in the macrosystem, and the integration ...
doi:10.1007/bf02745371
fatcat:sf2s2mm7nnapdaisce5ka5p6wi
Applied Machine Learning for Games: A Graduate School Course
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2012.01148v1 fatcat:nvc6rdm5w5bxfcoa52gmleoq4e
Graduate students enrolled in this course apply different fields of machine learning techniques such as computer vision, natural language processing, computer graphics, human computer interaction, robotics ...
In this paper, we describe our machine learning course designed for graduate students interested in applying recent advances of deep learning and reinforcement learning towards gaming. ...
Computer Vision and Natural Language Processing Learning to play from pixels have become a widely accepted approach for traning AI agents after DeepMinds paper of playing Atari with Deep Reinforcement ...
arXiv:2012.01148v2
fatcat:f44ln32jnbfhrearv234ylteru
Leadership in Public Health: New Competencies for the Future
2015
Frontiers in Public Health
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For public health and the healthcare delivery systems to act in concert, education should be structured to reinforce a collaborative approach. ...
In Contemporary Public Health, Keck, Scutchfield, and Holsinger call for changes in vision among those leading the evolution of healthcare from individualistic to community-wide approaches to improve health ...
doi:10.3389/fpubh.2015.00024
pmid:25767792
pmcid:PMC4341427
fatcat:d4alstwpcneajb4tu4qqsgc7sq
Object-oriented Targets for Visual Navigation using Rich Semantic Representations
[article]
2018
arXiv
pre-print
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When searching for an object humans navigate through a scene using semantic information and spatial relationships. ...
We look for an object using our knowledge of its attributes and relationships with other objects to infer the probable location. ...
[12] proposed a deep reinforcement learning framework for target-driven visual navigation. As input to the model, only the target frame is given without any other priors about the environment. ...
arXiv:1811.09178v2
fatcat:isc3ox3i5jd47pgjqvosrefavm
The origins of syntax: from navigation to language
2005
Connection science
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We suggest that the parser evolved for navigation might initially have been limited to handling regular languages, and describe a mechanism that may have created selective pressure for a context-free parser ...
We discuss two independent conjectures about the way in which navigation could have supported the emergence of this aspect of the human language faculty: firstly, by promoting the development of a parser ...
However, it is clear that a parser evolved for navigation could have benefited the evolution of a human language faculty by lending it its power to handle syntactic structure, regardless of the actual ...
doi:10.1080/09540090500282479
fatcat:6fmrgym7fjebhpuafvq4nyhbly
Survey on reinforcement learning for language processing
[article]
2022
arXiv
pre-print
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This paper reviews the state of the art of RL methods for their possible use for different problems of natural language processing, focusing primarily on conversational systems, mainly due to their growing ...
Finally, we elaborate on promising research directions in natural language processing that might benefit from reinforcement learning. ...
We thank Burhan Hafez for discussions and providing references highly relevant to this review. ...
arXiv:2104.05565v3
fatcat:hiwdpykddzhzzi3wqcv4hhknba
A Survey of Deep Learning Techniques for Mobile Robot Applications
[article]
2018
arXiv
pre-print
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This research survey will present a summarization of the current research with a specific focus on the gains and obstacles for deep learning to be applied to mobile robotics. ...
Within these models, distinct types of layers have undergone evolution for many aims. ...
Deep learning architectures for instance deep neural, deep beliefs as well as recurrent neural networks have been utilized in arenas inclusive of computer vision, natural language processing, social network ...
arXiv:1803.07608v1
fatcat:edwca3yd5fhcri3zkfdfg2o2ju
Learning to "brave up": Collaboration, agency, and authority in multicultural, multilingual, and radically inclusive classrooms
2018
International Journal of Multicultural Education
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The Summer Language Academy (SLA) is an innovative and intensive summer program for high-school aged newcomers/new Americans, English learners, and emergent bilinguals, as well as for teachers working ...
In the SLA, students and educators collaboratively explore questions of identity, language, and culture through high-interest texts, arts-based curriculum, and redefinition of teaching and learning as ...
Throughout the SLA, educators strategically and intentionally analyzed the role languages could play to either interrupt or reinforce linguistic inclusion. ...
doi:10.18251/ijme.v20i3.1670
fatcat:g5vcsftt7zclpgkb26yd6l4pza
The RobotSlang Benchmark: Dialog-guided Robot Localization and Navigation
[article]
2020
arXiv
pre-print
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Autonomous robot systems for applications from search and rescue to assistive guidance should be able to engage in natural language dialog with people. ...
We present an initial model for the NDH task, and show that an agent trained in simulation can follow the RobotSlang dialog-based navigation instructions for controlling a physical robot platform. ...
Vikas Dhiman for their substantive discussions that were fundamental to RobotSlang's evolution. ...
arXiv:2010.12639v1
fatcat:k53mcuuvmrghhivcmcyx63qiea
Page 965 of Psychological Abstracts Vol. 82, Issue 2
[page]
1995
Psychological Abstracts
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
Leonard
Evolution of a subsumption architecture that performs a wall following task for an autonomous mobile robot - John R. ...
Hollatz
Applications
Unsupervised learning for mobile robot navigation using prob- abilistic data association - Ingemar J. Cox and John J. ...
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