About: A multi-agent reinforcement learning model of common-pool resource appropriation

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: A multi-agent reinforcement learning model of common-pool resource appropriation Goto Sponge NotDistinct Permalink

An Entity of Type : wikibase:Item, within Data Space : wikidata.demo.openlinksw.com associated with source document(s)

scholarly article by Julien Pérolat et al published 2017 in Advances in Neural Information Processing Systems 30

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (gepubliceerd op 2017/01/01) (nl) наукова стаття, опублікована у 2017 (uk) article scientifique publié en 2017 (fr) scholarly article by Julien Pérolat et al published 2017 in Advances in Neural Information Processing Systems 30 (en)
publication date	wds:Q44649255-A1D97208-1372-4267-94BE-64F42BAE77CC
publication date	2017-01-01 00:00:00Z (xsd:dateTime)
language of work or name	wds:Q44649255-06D1E9AB-3C6A-48BC-AE57-2FCB8DF6307A
language of work or name	English
author name string	wds:Q44649255-07FC225F-09FF-4601-B6E7-65BDD896AA8F wds:Q44649255-60B8A05B-95C7-4101-8195-F21E333EB028 wds:Q44649255-7B588EF0-3CD9-47FC-A518-9695ED7DC6EB wds:Q44649255-A25175E8-54B6-4D9A-B7F3-844B94BCC900
author name string	Karl Tuyls Vinicius Zambaldi Julien Pérolat Charles Beattie
rdfs:label	A multi-agent reinforcement learning model of common-pool resource appropriation (en) A multi-agent reinforcement learning model of common-pool resource appropriation (nl)
skos:prefLabel	A multi-agent reinforcement learning model of common-pool resource appropriation (en) A multi-agent reinforcement learning model of common-pool resource appropriation (nl)
name	A multi-agent reinforcement learning model of common-pool resource appropriation (en) A multi-agent reinforcement learning model of common-pool resource appropriation (nl)
author	wds:Q44649255-08E491F9-E2F2-48FF-9B85-309467FCD0F5 wds:Q44649255-BF0609C6-0E0B-4563-BFD3-4834EA6C0806
author	Joel Z. Leibo Thore Graepel
title	wds:Q44649255-449D9699-45FC-44F8-BBEF-64D4E321E167
title	A multi-agent reinforcement learning model of common-pool resource appropriation (en)
instance of	wds:Q44649255-8A570CCC-A608-4E19-8C7E-FF86F6D83F12
instance of	scholarly article
main subject	wds:Q44649255-B1FD4C61-5E52-45CA-B7DC-04CE129AE390 wds:Q44649255-F5795364-B1AC-4042-B507-5E634B26A8BA
main subject	Multi-agent reinforcement learning reinforcement learning
published in	wds:Q44649255-A12887D4-1207-4D86-948E-842358C55DF8
full work available at URL	wds:Q44649255-ABED396B-7B3A-413A-A7DD-D77CA7464EBB
published in	Advances in Neural Information Processing Systems 30
full work available at URL	https://papers.nips.cc/paper/6955-a-multi-agent-reinforcement-learning-model-of-common-pool-resource-appropriation.pdf
official website	wds:Q44649255-402C495E-E39B-494A-89A6-0F2659B1A160
official website	https://papers.nips.cc/paper/6955-a-multi-agent-reinforcement-learning-model-of-common-pool-resource-appropriation
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q44649255

Faceted Search & Find service v1.16.117 as of May 05 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3239 as of May 5 2024, on Linux (x86_64-centos_6-linux-gnu), Single-Server Edition (378 GB total memory, 190 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software