Tutorial Abstracts Article Swipe
Automated Negotiation between intelligent agents is attracting more attention from the research community, especially with the broader market penetration of intelligent agents and the need to coordinate their behavior.Supply Chain Management is one of the core industrial technologies.Currently, SCM systems set targets that are then negotiated manually to reach agreements between suppliers and consumers and adjust these agreements based on market and operational conditions.Market studies suggest that in some industries, up to 15% of value is lost due to the inability to reach win-win optimal contracting conditions.The recent disruption of supply chains highlights the need to achieve dynamic supply chains capable of responding optimally to changes in market conditions.Automated Negotiation is a promising direction toward this goal.The International Automated Negotiating Agents Competition (ANAC) has provided stimulation for AN research since its introduction in 2010.Since 2019, a new league was added to ANAC focusing on applying automated Negotiation in a realistic business-like Supply Chain Management scenario (SCML).The main goal of the SCM league is to bring automated negotiation research more toward the real world by putting Negotiation into a larger context from which endogenous utility functions are created instead of being predefined.This game provides ample opportunities for novel ideas in concurrent Negotiation, utility function design, and applying machine learning techniques to automated Negotiation.This tutorial introduces the audience to automated Negotiation, its application to supply chain management, and the SCML competition.It walks them through developing an agent for the competition, highlighting the research challenges.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/ica58824.2023.00009
- https://ieeexplore.ieee.org/ielx7/10405363/10405383/10405366.pdf
- OA Status
- gold
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- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391306675Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/ica58824.2023.00009Digital Object Identifier
- Title
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Tutorial AbstractsWork title
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articleOpenAlex work type
- Language
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enPrimary language
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2023Year of publication
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2023-12-04Full publication date if available
- Authors
-
Yasser MohammadList of authors in order
- Landing page
-
https://doi.org/10.1109/ica58824.2023.00009Publisher landing page
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-
https://ieeexplore.ieee.org/ielx7/10405363/10405383/10405366.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/10405363/10405383/10405366.pdfDirect OA link when available
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Negotiation, Supply chain, Computer science, Context (archaeology), Competition (biology), Supply chain management, Process management, Knowledge management, Function (biology), Business, Marketing, Paleontology, Law, Biology, Evolutionary biology, Political science, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.introduction | 131 |
| abstract_inverted_index.International | 117 |
| abstract_inverted_index.business-like | 150 |
| abstract_inverted_index.opportunities | 194 |
| abstract_inverted_index.competition.It | 228 |
| abstract_inverted_index.conditions.The | 86 |
| abstract_inverted_index.behavior.Supply | 28 |
| abstract_inverted_index.predefined.This | 190 |
| abstract_inverted_index.Negotiation.This | 211 |
| abstract_inverted_index.conditions.Market | 63 |
| abstract_inverted_index.conditions.Automated | 108 |
| abstract_inverted_index.technologies.Currently, | 37 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5007758273 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 1 |
| corresponding_institution_ids | https://openalex.org/I118347220, https://openalex.org/I73613424, https://openalex.org/I91041137 |
| citation_normalized_percentile.value | 0.32261605 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |