Synthesis of controllable nash equilibria in games with quantitative objectives
In Rational Synthesis, we consider a multi-agent system in which some of the agents are controllable and some are not. All agents have objectives, and the goal is to synthesize strategies for the controllable agents so that their objectives are satisfied, assuming rationality of the uncontrollable a...
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| Format: | Conference item |
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International Joint Conferences on Artificial Intelligence Organization
2018
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| _version_ | 1826293222109872128 |
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| author | Almagor, S Kupferman, O Perelli, G |
| author_facet | Almagor, S Kupferman, O Perelli, G |
| author_sort | Almagor, S |
| collection | OXFORD |
| description | In Rational Synthesis, we consider a multi-agent system in which some of the agents are controllable and some are not. All agents have objectives, and the goal is to synthesize strategies for the controllable agents so that their objectives are satisfied, assuming rationality of the uncontrollable agents. Previous work on rational synthesis considers objectives in LTL, namely ones that describe on-going behaviors, and in Objective-LTL, which allows ranking of LTL formulas. In this paper, we extend rational synthesis to LTL[F]– an extension of LTL by quality operators. The satisfaction value of an LTL[F] formula is a real value in [0; 1], where the higher the value is, the higher is the quality in which the computation satisfies the specification. The extension significantly strengthens the framework of rational synthesis and enables a study its game- and socialchoice theoretic aspects. In particular, we study the price of stability and price of anarchy of the rationalsynthesis game and use them to explain the cooperative and non-cooperative settings of rational synthesis. Our algorithms make use of strategy logic and decision procedures for it. Thus, we are able to handle the richer quantitative setting using existing tools. In particular, we show that the cooperative and non-cooperative versions of quantitative rational synthesis are 2EXPTIMEcomplete and in 3EXPTIME, respectively – not harder than the complexity known for their Boolean analogues. |
| first_indexed | 2024-03-07T03:26:47Z |
| format | Conference item |
| id | oxford-uuid:b94cd6d4-0759-45cc-89c6-e73a9d97b0b5 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T03:26:47Z |
| publishDate | 2018 |
| publisher | International Joint Conferences on Artificial Intelligence Organization |
| record_format | dspace |
| spelling | oxford-uuid:b94cd6d4-0759-45cc-89c6-e73a9d97b0b52022-03-27T05:02:02ZSynthesis of controllable nash equilibria in games with quantitative objectivesConference itemhttp://purl.org/coar/resource_type/c_5794uuid:b94cd6d4-0759-45cc-89c6-e73a9d97b0b5Symplectic Elements at OxfordInternational Joint Conferences on Artificial Intelligence Organization2018Almagor, SKupferman, OPerelli, GIn Rational Synthesis, we consider a multi-agent system in which some of the agents are controllable and some are not. All agents have objectives, and the goal is to synthesize strategies for the controllable agents so that their objectives are satisfied, assuming rationality of the uncontrollable agents. Previous work on rational synthesis considers objectives in LTL, namely ones that describe on-going behaviors, and in Objective-LTL, which allows ranking of LTL formulas. In this paper, we extend rational synthesis to LTL[F]– an extension of LTL by quality operators. The satisfaction value of an LTL[F] formula is a real value in [0; 1], where the higher the value is, the higher is the quality in which the computation satisfies the specification. The extension significantly strengthens the framework of rational synthesis and enables a study its game- and socialchoice theoretic aspects. In particular, we study the price of stability and price of anarchy of the rationalsynthesis game and use them to explain the cooperative and non-cooperative settings of rational synthesis. Our algorithms make use of strategy logic and decision procedures for it. Thus, we are able to handle the richer quantitative setting using existing tools. In particular, we show that the cooperative and non-cooperative versions of quantitative rational synthesis are 2EXPTIMEcomplete and in 3EXPTIME, respectively – not harder than the complexity known for their Boolean analogues. |
| spellingShingle | Almagor, S Kupferman, O Perelli, G Synthesis of controllable nash equilibria in games with quantitative objectives |
| title | Synthesis of controllable nash equilibria in games with quantitative objectives |
| title_full | Synthesis of controllable nash equilibria in games with quantitative objectives |
| title_fullStr | Synthesis of controllable nash equilibria in games with quantitative objectives |
| title_full_unstemmed | Synthesis of controllable nash equilibria in games with quantitative objectives |
| title_short | Synthesis of controllable nash equilibria in games with quantitative objectives |
| title_sort | synthesis of controllable nash equilibria in games with quantitative objectives |
| work_keys_str_mv | AT almagors synthesisofcontrollablenashequilibriaingameswithquantitativeobjectives AT kupfermano synthesisofcontrollablenashequilibriaingameswithquantitativeobjectives AT perellig synthesisofcontrollablenashequilibriaingameswithquantitativeobjectives |