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| Format: | Preprint |
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2024
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| Online Access: | https://arxiv.org/abs/2403.05103 |
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| _version_ | 1866916623342895104 |
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| author | DiGiovanni, Anthony Clifton, Jesse Macé, Nicolas |
| author_facet | DiGiovanni, Anthony Clifton, Jesse Macé, Nicolas |
| contents | Agents in mixed-motive coordination problems such as Chicken may fail to coordinate on a Pareto-efficient outcome. Safe Pareto improvements (SPIs) were originally proposed to mitigate miscoordination in cases where players lack probabilistic beliefs as to how their delegates will play a game; delegates are instructed to behave so as to guarantee a Pareto improvement on how they would play by default. More generally, SPIs may be defined as transformations of strategy profiles such that all players are necessarily better off under the transformed profile. In this work, we investigate the extent to which SPIs can reduce downsides of miscoordination between expected utility-maximizing agents. We consider games in which players submit computer programs that can condition their decisions on each other's code, and use this property to construct SPIs using programs capable of renegotiation. We first show that under mild conditions on players' beliefs, each player always prefers to use renegotiation. Next, we show that under similar assumptions, each player always prefers to be willing to renegotiate at least to the point at which they receive the lowest payoff they can attain in any efficient outcome. Thus subjectively optimal play guarantees players at least these payoffs, without the need for coordination on specific Pareto improvements. Lastly, we prove that renegotiation does not guarantee players any improvements on this bound. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_05103 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Safe Pareto Improvements for Expected Utility Maximizers in Program Games DiGiovanni, Anthony Clifton, Jesse Macé, Nicolas Computer Science and Game Theory Agents in mixed-motive coordination problems such as Chicken may fail to coordinate on a Pareto-efficient outcome. Safe Pareto improvements (SPIs) were originally proposed to mitigate miscoordination in cases where players lack probabilistic beliefs as to how their delegates will play a game; delegates are instructed to behave so as to guarantee a Pareto improvement on how they would play by default. More generally, SPIs may be defined as transformations of strategy profiles such that all players are necessarily better off under the transformed profile. In this work, we investigate the extent to which SPIs can reduce downsides of miscoordination between expected utility-maximizing agents. We consider games in which players submit computer programs that can condition their decisions on each other's code, and use this property to construct SPIs using programs capable of renegotiation. We first show that under mild conditions on players' beliefs, each player always prefers to use renegotiation. Next, we show that under similar assumptions, each player always prefers to be willing to renegotiate at least to the point at which they receive the lowest payoff they can attain in any efficient outcome. Thus subjectively optimal play guarantees players at least these payoffs, without the need for coordination on specific Pareto improvements. Lastly, we prove that renegotiation does not guarantee players any improvements on this bound. |
| title | Safe Pareto Improvements for Expected Utility Maximizers in Program Games |
| topic | Computer Science and Game Theory |
| url | https://arxiv.org/abs/2403.05103 |