Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
166 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Incentive Engineering for Concurrent Games (2307.05076v1)

Published 11 Jul 2023 in cs.GT, cs.LO, and cs.MA

Abstract: We consider the problem of incentivising desirable behaviours in multi-agent systems by way of taxation schemes. Our study employs the concurrent games model: in this model, each agent is primarily motivated to seek the satisfaction of a goal, expressed as a Linear Temporal Logic (LTL) formula; secondarily, agents seek to minimise costs, where costs are imposed based on the actions taken by agents in different states of the game. In this setting, we consider an external principal who can influence agents' preferences by imposing taxes (additional costs) on the actions chosen by agents in different states. The principal imposes taxation schemes to motivate agents to choose a course of action that will lead to the satisfaction of their goal, also expressed as an LTL formula. However, taxation schemes are limited in their ability to influence agents' preferences: an agent will always prefer to satisfy its goal rather than otherwise, no matter what the costs. The fundamental question that we study is whether the principal can impose a taxation scheme such that, in the resulting game, the principal's goal is satisfied in at least one or all runs of the game that could arise by agents choosing to follow game-theoretic equilibrium strategies. We consider two different types of taxation schemes: in a static scheme, the same tax is imposed on a state-action profile pair in all circumstances, while in a dynamic scheme, the principal can choose to vary taxes depending on the circumstances. We investigate the main game-theoretic properties of this model as well as the computational complexity of the relevant decision problems.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (42)
  1. In: 19th International Conference on Principles of Knowledge Representation and Reasoning, KR 2022: KR 2022, 10.24963/kr.2022/2.
  2. Rajeev Alur, Thomas A. Henzinger & Orna Kupferman (2002): Alternating-time temporal logic. J. ACM 49(5), pp. 672–713, 10.1145/585265.585270.
  3. arXiv preprint arXiv:2202.10135, 10.48550/arXiv.2202.10135.
  4. European Journal of Operational Research 258(1), pp. 295–306, 10.1016/j.ejor.2016.08.055.
  5. Nils Bulling & Mehdi Dastani (2016): Norm-based mechanism design. Artificial Intelligence 239, pp. 97–142, 10.1016/j.artint.2016.07.001.
  6. Henrique Lopes Cardoso & Eugénio Oliveira (2009): Adaptive Deterrence Sanctions in a Normative Framework. In: 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, 2, pp. 36–43, 10.1109/WI-IAT.2009.123.
  7. Roberto Centeno & Holger Billhardt (2011): Using incentive mechanisms for an adaptive regulation of open multi-agent systems. In: Twenty-Second International Joint Conference on Artificial Intelligence, 10.5591/978-1-57735-516-8/IJCAI11-035.
  8. Krishnendu Chatterjee, Thomas A. Henzinger & Marcin Jurdzinski (2005): Mean-Payoff Parity Games. In: 20th IEEE Symposium on Logic in Computer Science (LICS 2005), 26-29 June 2005, Chicago, IL, USA, Proceedings, IEEE Computer Society, pp. 178–187, 10.1109/LICS.2005.26.
  9. Davide Dell’Anna, Mehdi Dastani & Fabiano Dalpiaz (2020): Runtime Revision of Sanctions in Normative Multi-Agent Systems. Autonomous Agents and Multi-Agent Systems 34(2), 10.1007/s10458-020-09465-8.
  10. Neural Computing and Applications, pp. 1–17, 10.1007/s00521-022-07396-x.
  11. E. Allen Emerson (1990): Temporal and Modal Logic. In Jan van Leeuwen, editor: Handbook of Theoretical Computer Science, Volume B: Formal Models and Semantics, Elsevier and MIT Press, pp. 995–1072, 10.1016/b978-0-444-88074-1.50021-4.
  12. Dana Fisman, Orna Kupferman & Yoad Lustig (2010): Rational synthesis. In: International Conference on Tools and Algorithms for the Construction and Analysis of Systems, Springer, pp. 190–204, 10.1007/978-3-642-12002-2_16.
  13. Sanford J. Grossman & Oliver D. Hart (1992): An analysis of the principal-agent problem. In: Foundations of insurance economics, Springer, pp. 302–340, 10.1007/978-94-015-7957-5_16.
  14. Julian Gutierrez, Paul Harrenstein & Michael J. Wooldridge (2017): Reasoning about equilibria in game-like concurrent systems. Annals of Pure and Applied Logic 169(2), pp. 373–403, 10.1016/j.apal.2016.10.009.
  15. Acta Informatica 58(6), pp. 585–610, 10.1007/s00236-020-00385-4.
  16. In: 30th International Conference on Concurrency Theory, 10.4230/LIPIcs.CONCUR.2019.22.
  17. Artificial Intelligence 287, p. 103353, 10.1016/j.artint.2020.103353.
  18. Paul Harrenstein, Paolo Turrini & Michael J. Wooldridge (2014): Hard and soft equilibria in boolean games. In Ana L. C. Bazzan, Michael N. Huhns, Alessio Lomuscio & Paul Scerri, editors: International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France, May 5-9, 2014, IFAAMAS/ACM, pp. 845–852, 10.5555/2615731.2615867. Available at http://dl.acm.org/citation.cfm?id=2615867.
  19. Paul Harrenstein, Paolo Turrini & Michael J. Wooldridge (2017): Characterising the Manipulability of Boolean Games. In Carles Sierra, editor: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017, ijcai.org, pp. 1081–1087, 10.24963/ijcai.2017/150.
  20. Bengt Holmstrom (1982): Moral hazard in teams. The Bell journal of economics, pp. 324–340, 10.2307/3003457.
  21. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI’16, AAAI Press, p. 1123–1129.
  22. Kenneth S. Lyon & Dug Man Lee (2001): Pigouvian tax and the congestion externality: a benefit side approach. Economics Research Institute Study Paper 10, p. 1.
  23. The Scientific World Journal 2014, 10.1155/2014/684587.
  24. N. Gregory Mankiw (2009): Smart taxes: An open invitation to join the pigou club. Eastern Economic Journal 35(1), pp. 14–23, 10.1057/EEJ.2008.43.
  25. In: Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning, 18, pp. 487–496, 10.24963/kr.2021/46.
  26. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, p. 386–394.
  27. David Mguni & Marcin Tomczak (2019): Efficient reinforcement dynamic mechanism design. In: GAIW: Games, agents and incentives workshops, at AAMAS, Montreal, Canada.
  28. In: 31st International Joint Conference on Artificial Intelligence (IJCAI-22), International Joint Conferences on Artificial Intelligence Organization, pp. 426–432, 10.24963/ijcai.2022/61.
  29. Proc. of the Adaptive and Learning Agents Workshop (ALA 2022).
  30. Ai Magazine 31(4), pp. 79–94, 10.1609/aimag.v31i4.2316.
  31. Giuseppe Perelli (2019): Enforcing equilibria in multi-agent systems. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, pp. 188–196, 10.5555/3306127.3331692.
  32. Arthur C. Pigou & Nahid Aslanbeigui (2017): The Economics of Welfare. Routledge, 10.4324/9781351304368.
  33. Amir Pnueli (1977): The Temporal Logic of Programs. In: 18th Annual Symposium on Foundations of Computer Science, Providence, Rhode Island, USA, 31 October - 1 November 1977, IEEE Computer Society, pp. 46–57, 10.1109/SFCS.1977.32.
  34. Amir Pnueli & Roni Rosner (1989): On the Synthesis of an Asynchronous Reactive Module. In Giorgio Ausiello, Mariangiola Dezani-Ciancaglini & Simona Ronchi Della Rocca, editors: Automata, Languages and Programming, 16th International Colloquium, ICALP89, Stresa, Italy, July 11-15, 1989, Proceedings, Lecture Notes in Computer Science 372, Springer, pp. 652–671, 10.1007/BFb0035790.
  35. Annual Review of Control, Robotics, and Autonomous Systems 2, pp. 305–338, 10.1146/ANNUREV-CONTROL-053018-023634.
  36. Lillian J Ratliff & Tanner Fiez (2020): Adaptive incentive design. IEEE Transactions on Automatic Control 66(8), pp. 3871–3878, 10.1109/tac.2020.3027503.
  37. Weiran Shen, Pingzhong Tang & Song Zuo (2019): Automated Mechanism Design via Neural Networks. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, p. 215–223, 10.5555/3306127.3331696.
  38. A. Prasad Sistla & Edmund M. Clarke (1985): The Complexity of Propositional Linear Temporal Logics. J. ACM 32(3), pp. 733–749, 10.1145/3828.3837.
  39. Michael Ummels & Dominik Wojtczak (2011): The complexity of Nash equilibria in limit-average games. In: International Conference on Concurrency Theory, Springer, pp. 482–496, 10.1007/978-3-642-23217-6_32.
  40. Artif. Intell. 195, pp. 418–439, 10.1016/j.artint.2012.11.003.
  41. In Dale Schuurmans & Michael P. Wellman, editors: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA, AAAI Press, pp. 4184–4191, 10.1016/J.ARTINT.2017.04.003. Available at http://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/view/12268.
  42. arXiv preprint arXiv:2112.10859, 10.5555/3535850.3536010.
Citations (2)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now