Abstract
We study the situation of an exogenous decisionmaker aiming to encourage a population of autonomous, self-regarding agents to follow a desired behaviour at a minimal cost. The primary goal is therefore to reach an efficient trade-off between pushing the agents to achieve the desired configuration while minimising the total investment. To this end, we test several interference paradigms resorting to simulations of agents facing a cooperative dilemma in a spatial arrangement. We systematically analyse and compare interference strategies rewarding local or global behavioural patterns. Our results show that taking into account the neighbourhood’s local properties, such as its level of cooperativeness, can lead to a significant improvement regarding cost efficiency while guaranteeing high levels of cooperation. As such, we argue that local interference strategies are more efficient than global ones in fostering cooperation in a population of autonomous agents.
Original language | English |
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Title of host publication | Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence |
Publisher | IJCAI |
Pages | 289-295 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 20 Jul 2018 |
Event | 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence - Stockholmsmässan, Stockholm, Sweden Duration: 13 Jul 2018 → 19 Jul 2018 http://www.ijcai-18.org/ |
Publication series
Name | Proceedings (IITA International Joint Conference on Artificial Intelligence) |
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ISSN (Electronic) | 2162-1160 |
Conference
Conference | 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence |
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Abbreviated title | IJCAI-ECAI-18 |
Country/Territory | Sweden |
City | Stockholm |
Period | 13/07/18 → 19/07/18 |
Internet address |
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The Anh Han
- Department of Computing & Games - Professor (Computer Science)
- Centre for Digital Innovation
Person: Professorial, Academic