aiqbench analysis
This article introduces "Automated Negotiation," which falls under multiagent systems and game theory, core subfields of artificial intelligence rather than consumer tech or general software events. The content focuses on educational resources for implementing negotiation algorithms using Python frameworks to facilitate research in AI-driven decision-making processes.
Introduction to Automated Negotiation
arXiv:2511.08659v5 Announce Type: replace-cross Abstract: This book is an introductory textbook targeted towards computer science students who are completely new to the topic of automated negotiation. It does not require any prerequisite knowledge, except for elementary mathematics and basic programming skills. This book comes with an simple toy-world negotiation framework implemented in Python that can be used by the readers to implement their own negotiation algorithms and perform experiments with them. This framework is small and simple enough that any reader who does not like to work in Python should be able to re-implement it very quickly in any other programming language of their choice.
arXiv:2511.08659 (cs)
Abstract:This book is an introductory textbook targeted towards computer science students who are completely new to the topic of automated negotiation. It does not require any prerequisite knowledge, except for elementary mathematics and basic programming skills. This book comes with an simple toy-world negotiation framework implemented in Python that can be used by the readers to implement their own negotiation algorithms and perform experiments with them. This framework is small and simple enough that any reader who does not like to work in Python should be able to re-implement it very quickly in any other programming language of their choice.
Multiagent Systems (cs.MA); Artificial Intelligence (cs.AI); Computer Science and Game Theory (cs.GT)
arXiv:2511.08659 [cs.MA]
(or arXiv:2511.08659v5 [cs.MA] for this version)
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Full text under the publisher's open licence · 194 words
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