NeuroGenesysThe research we build on.
1,514 papers by other researchers that our work cites, from continual learning and verification to language models, agents and hardware. Each entry links to the paper on arXiv and to where we use it. 301 are cited on published pages of this site; the rest in the research notes behind our studies. Our own papers are in the archive.
- 2021-02arXiv 2102.06284Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients
Arbaaz Khan, Vijay Kumar, Alejandro Ribeiro · Robotics & control
In this paper, we present a learning method to solve the unlabelled motion problem with motion constraints and space constraints in 2D space for a large number of robots.
Cited inStudy: Arvind Gupta meeting prep - 2019-07arXiv 1907.03822Graph Policy Gradients for Large Scale Robot Control
Arbaaz Khan, Ekaterina Tolstaya, Alejandro Ribeiro et al. · Robotics & control
In this paper, we consider the problem of learning policies to control a large number of homogeneous robots. To this end, we propose a new algorithm we call Graph Policy Gradients (GPG) that exploits the underlying graph symmetry among the robots.
Cited inStudy: Arvind Gupta meeting prep
Built from every arXiv paper cited in our papers, posts, topic hubs, reports and research notes, with titles, authors, dates and abstracts from the arXiv API (updated 2026-11-12). Summaries are the opening sentences of each paper's own abstract, not our assessment; a citation means we used or checked the work, not that we endorse it. Fields follow each paper's primary arXiv category. Papers cited only outside arXiv (journals, proceedings) are not listed yet. Entries are generated from our citations, so a mistyped ID in a note would list the wrong paper; we remove those as we find them. Report a wrong entry.
