Learning to Communicate with Strangers via Channel Randomisation Methods
4th Workshop on Emergent Communication at NeurIPS 2020 We introduce two methods for improving the performance of agents meeting for the first time to accomplish a communicative task. The methods are: (1) `message mutation' during the generation of the communication protocol; and (2) random perm...
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creator | Cope, Dylan Schoots, Nandi |
description | 4th Workshop on Emergent Communication at NeurIPS 2020 We introduce two methods for improving the performance of agents meeting for
the first time to accomplish a communicative task. The methods are: (1)
`message mutation' during the generation of the communication protocol; and (2)
random permutations of the communication channel. These proposals are tested
using a simple two-player game involving a `teacher' who generates a
communication protocol and sends a message, and a `student' who interprets the
message. After training multiple agents via self-play we analyse the
performance of these agents when they are matched with a stranger, i.e. their
zero-shot communication performance. We find that both message mutation and
channel permutation positively influence performance, and we discuss their
effects. |
doi_str_mv | 10.48550/arxiv.2104.09557 |
format | Article |
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the first time to accomplish a communicative task. The methods are: (1)
`message mutation' during the generation of the communication protocol; and (2)
random permutations of the communication channel. These proposals are tested
using a simple two-player game involving a `teacher' who generates a
communication protocol and sends a message, and a `student' who interprets the
message. After training multiple agents via self-play we analyse the
performance of these agents when they are matched with a stranger, i.e. their
zero-shot communication performance. We find that both message mutation and
channel permutation positively influence performance, and we discuss their
effects.</description><identifier>DOI: 10.48550/arxiv.2104.09557</identifier><language>eng</language><subject>Computer Science - Artificial Intelligence ; Computer Science - Computation and Language ; Computer Science - Learning</subject><creationdate>2021-04</creationdate><rights>http://creativecommons.org/licenses/by/4.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2104.09557$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2104.09557$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Cope, Dylan</creatorcontrib><creatorcontrib>Schoots, Nandi</creatorcontrib><title>Learning to Communicate with Strangers via Channel Randomisation Methods</title><description>4th Workshop on Emergent Communication at NeurIPS 2020 We introduce two methods for improving the performance of agents meeting for
the first time to accomplish a communicative task. The methods are: (1)
`message mutation' during the generation of the communication protocol; and (2)
random permutations of the communication channel. These proposals are tested
using a simple two-player game involving a `teacher' who generates a
communication protocol and sends a message, and a `student' who interprets the
message. After training multiple agents via self-play we analyse the
performance of these agents when they are matched with a stranger, i.e. their
zero-shot communication performance. We find that both message mutation and
channel permutation positively influence performance, and we discuss their
effects.</description><subject>Computer Science - Artificial Intelligence</subject><subject>Computer Science - Computation and Language</subject><subject>Computer Science - Learning</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz7FOwzAUhWEvDKjtAzDhF0hwHDuOxyqiLVIQEmWPbu3rxlJjI8ct8PZAYTrTf6SPkLuKlaKVkj1A-vSXkldMlExLqW7JrkdIwYcjzZF2cZrOwRvISD98Huk-JwhHTDO9eKDdCCHgib5CsHHyM2QfA33GPEY7L8mNg9OMq_9dkP3m8a3bFf3L9qlb9wU0ShXCWNNYrLiAqm615sI0WigHKK1tWdMqDcYhc1gDr4UTlnMDUh-UYYefZEHu_16vkuE9-QnS1_ArGq6i-huu60dT</recordid><startdate>20210419</startdate><enddate>20210419</enddate><creator>Cope, Dylan</creator><creator>Schoots, Nandi</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20210419</creationdate><title>Learning to Communicate with Strangers via Channel Randomisation Methods</title><author>Cope, Dylan ; Schoots, Nandi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a677-4cdc6de124a1389924c6947fae5dd806879acfe0fe3a234f4d22ca59b7c0ba13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Artificial Intelligence</topic><topic>Computer Science - Computation and Language</topic><topic>Computer Science - Learning</topic><toplevel>online_resources</toplevel><creatorcontrib>Cope, Dylan</creatorcontrib><creatorcontrib>Schoots, Nandi</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Cope, Dylan</au><au>Schoots, Nandi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Learning to Communicate with Strangers via Channel Randomisation Methods</atitle><date>2021-04-19</date><risdate>2021</risdate><abstract>4th Workshop on Emergent Communication at NeurIPS 2020 We introduce two methods for improving the performance of agents meeting for
the first time to accomplish a communicative task. The methods are: (1)
`message mutation' during the generation of the communication protocol; and (2)
random permutations of the communication channel. These proposals are tested
using a simple two-player game involving a `teacher' who generates a
communication protocol and sends a message, and a `student' who interprets the
message. After training multiple agents via self-play we analyse the
performance of these agents when they are matched with a stranger, i.e. their
zero-shot communication performance. We find that both message mutation and
channel permutation positively influence performance, and we discuss their
effects.</abstract><doi>10.48550/arxiv.2104.09557</doi><oa>free_for_read</oa></addata></record> |
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subjects | Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Learning |
title | Learning to Communicate with Strangers via Channel Randomisation Methods |
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