dorsal/arxiv
View SchemaSpatial snowdrift game with myopic agents
| Authors | Marko Sysi-Aho, Jari Saramaki, Janos Kertesz, Kimmo Kaski |
|---|---|
| Categories | |
| ArXiv ID | physics/0411091 |
| URL | https://arxiv.org/abs/physics/0411091 |
| DOI | 10.1140/epjb/e2005-00108-5 |
Abstract
We have studied a spatially extended snowdrift game, in which the players are located on the sites of two-dimensional square lattices and repeatedly have to choose one of the two strategies, either cooperation (C) or defection (D). A player interacts with its nearest neighbors only, and aims at playing a strategy which maximizes its instant pay-off, assuming that the neighboring agents retain their strategies. If a player is not content with its current strategy, it will change it to the opposite one with probability $p$ next round. Here we show through simulations and analytical approach that these rules result in cooperation levels, which differ to large extent from those obtained using the replicator dynamics.
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"abstract": "We have studied a spatially extended snowdrift game, in which the players are\nlocated on the sites of two-dimensional square lattices and repeatedly have to\nchoose one of the two strategies, either cooperation (C) or defection (D). A\nplayer interacts with its nearest neighbors only, and aims at playing a\nstrategy which maximizes its instant pay-off, assuming that the neighboring\nagents retain their strategies. If a player is not content with its current\nstrategy, it will change it to the opposite one with probability $p$ next\nround. Here we show through simulations and analytical approach that these\nrules result in cooperation levels, which differ to large extent from those\nobtained using the replicator dynamics.",
"arxiv_id": "physics/0411091",
"authors": [
"Marko Sysi-Aho",
"Jari Saramaki",
"Janos Kertesz",
"Kimmo Kaski"
],
"categories": [
"physics.bio-ph"
],
"doi": "10.1140/epjb/e2005-00108-5",
"title": "Spatial snowdrift game with myopic agents",
"url": "https://arxiv.org/abs/physics/0411091"
},
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