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  • alves2022adleapmas

    Rights statement: © ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022 http://doi.acm.org/10.1145/3535850.3536143

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AdLeap-MAS: An Open-source Multi-Agent Simulator for Ad-hoc Reasoning: Demonstration Track

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date9/05/2022
Host publicationAAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems
Place of PublicationNew York
PublisherACM
Pages1893-1895
Number of pages3
ISBN (electronic)9781450392136
<mark>Original language</mark>English
EventInternational Conference on Autonomous Agents and Multiagent Systems 2022 - Online, Aukland, New Zealand
Duration: 9/05/202213/05/2022
https://aamas2022-conference.auckland.ac.nz/

Conference

ConferenceInternational Conference on Autonomous Agents and Multiagent Systems 2022
Abbreviated titleAAMAS 2022
Country/TerritoryNew Zealand
CityAukland
Period9/05/2213/05/22
Internet address

Conference

ConferenceInternational Conference on Autonomous Agents and Multiagent Systems 2022
Abbreviated titleAAMAS 2022
Country/TerritoryNew Zealand
CityAukland
Period9/05/2213/05/22
Internet address

Abstract

Ad-hoc reasoning models are recurrently used to solve some of our daily tasks. Intending to avoid worthless investments or spend valuable resources, these smart systems requires a proper evaluation before acting in the real-world. In this paper, we demonstrate AdLeap-MAS, a novel framework focused on enabling quick and easy testing of smart algorithms in ad-hoc reasoning domains.

Bibliographic note

© ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in AAMAS '22: Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022 http://doi.acm.org/10.1145/3535850.3536143