Algorithms for Life: Game Theory — Sources

[R01] Camerer & Ho (1999), 'Experience-Weighted Attraction Learning in Normal Form Games,' Econometrica 67(4):827–874 — meta-analysis of 122 experimental studies on Nash convergence.
[R02] Güth, Schmittberger & Schwarze (1982), 'An Experimental Analysis of Ultimatum Bargaining,' Journal of Economic Behavior & Organization 3:367–388.
[R03] McKelvey & Palfrey (1995), 'Quantal Response Equilibria for Normal Form Games,' Games and Economic Behavior 10:6–38.
[R04] arXiv:2506.09390 (2025), 'Beyond Nash Equilibrium: Bounded Rationality of LLMs and Humans in Strategic Games.'
[R05] Camerer (2003), Behavioral Game Theory, Princeton University Press — comprehensive synthesis of experimental findings across game types.
[R06] Tang (n.d.), Flevy consulting case study — Fortune 500 game theory consulting approach; FasterCapital (n.d.) — Nash equilibrium in startup strategy.
[R07] Rapoport & Chammah (1965), Prisoner's Dilemma, University of Michigan Press — foundational PD experimental baselines.
[R08] Sally (1995), 'Conversation and Cooperation in Social Dilemmas,' Rationality and Society 7:58–92 — meta-analysis of communication and cooperation.
[R09] Fehr & Gächter (2002), 'Altruistic Punishment in Humans,' Nature 415:137–140.
[R10] Axelrod (1984), The Evolution of Cooperation, Basic Books — foundational iterated PD tournament research.
[R11] Nowak & Sigmund (1992, 1993), 'Tit for Tat in Heterogeneous Populations' and 'A Strategy of Win-Stay, Lose-Shift,' Nature.
[R12] Press & Dyson (2012), 'Iterated Prisoner's Dilemma Contains Strategies That Dominate Any Evolutionary Opponent,' PNAS 109:10409–10413.
[R13] Hilbe et al. (2013), 'Evolution of Extortion in Iterated Prisoner's Dilemma Games,' PNAS 110:6913–6918.
[R14] Fischbacher, Gächter & Fehr (2001), 'Are People Conditionally Cooperative?' AER 91(5):1340–1349.
[R15] Nikiforakis (2008), 'Punishment and Counter-Punishment in Public Good Games,' AER 98(4):1319–1329.
[R16] Henrich et al. (2010), 'Markets, Religion, Community Size, and the Evolution of Fairness and Punishment,' Science 328:1480–1484.
[R17] Roth, Sönmez & Ünür (2004/2005), AER/Econometrica — kidney exchange algorithm design; Abdulkadiroğlu et al. (2005), Econometrica — school choice mechanism design.
[R18] Pathak & Sönmez (2008), 'Leveling the Playing Field: Sincere and Sophisticated Players in the Boston Mechanism,' AER — strategic misreporting in school choice.
[R19] Terrier, Pathak & Ren (2021), longitudinal study of England school matching post-Deferred Acceptance reform.
[R20] CEPEO / Nuffield Foundation, FSM quota simulation modeling for English school admissions equity.
[R21] AGCOM Italy 5G auction analysis (2018) — comparative UK/Italy auction data on 3.7 GHz band pricing.
[R22] BNetzA Germany 5G auction records (2019) + 2025 German court rulings on spectrum award validity.
[R23] Sandel, 'How Markets Crowd Out Morals,' Boston Review; Heyman & Ariely (2004) — crowding out of intrinsic motivation.
[R24] Akerlof (1970), 'The Market for Lemons,' QJE 84:488–500; Spence (1973), job-market signaling.
[R25] Brogaard et al. (2018), 'High-Frequency Trading and Information Asymmetry,' Review of Financial Studies 31:147–199.
[R26] Empirical health insurance research on adverse selection and moral hazard — multiple sources including RAND working papers and Baker Institute analysis.
[R27] Resnick et al. (2006), 'The Value of Reputation on eBay,' Management Science 52:1494–1505.
[R28] Gneezy (2005), 'Deception: The Role of Consequences,' AER 95(1):384–394.
[R29] Koutsoupias & Papadimitriou (1999), STOC — price of anarchy formalization; Roughgarden (2003), JCSS — selfish routing PoA bounds.
[R30] Braess's Paradox empirical and simulation evidence — transportation network studies on adding road capacity worsening congestion.
[R31] DOJ v. RealPage complaint (August 2024, amended January 2025) + consent decree (late 2025) — algorithmic rental pricing collusion.
[R32] FTC v. Amazon / Project Nessie federal complaint and district court ruling (2023) — algorithmic price manipulation.
[R33] Senator Klobuchar, Preventing Algorithmic Collusion Act (S. 232, reintroduced 2025).
[R34] Calvano et al. (SSRN/arXiv) — algorithmic collusion via Q-learning pricing agents; 2025 antitrust reviews.
[R35] EU AI Act text — formally effective August 2024, Articles 9 and Annex III on high-risk AI system governance.
[R36] UN CDM monitoring reports on HFC-23 loophole; European Commission HFC-23 ban documentation (post-April 2013).
[R37] England Organ Donation (Deemed Consent) Act implementation data (post-May 2020); NHS Blood and Transplant evaluation.
[R38] Iran compensated kidney donation literature — Kidney Foundation of Iran (KFI) descriptive and ethical accounts.
[R39] arXiv:2412.10270 (2024), 'Cultural Evolution of Cooperation among LLM Agents.'
[R40] Moonlight literature review of Willis et al. (2026), 'Will Systems of LLM Agents Cooperate?' — IPD tournaments with ChatGPT-4o and Claude 3.5 Sonnet.
[R41] Leibo et al. (2017), DeepMind — multi-agent deep RL emergent cooperation in iterated games.
[R42] Shah (2025), 'Game Theory in Ride-Sharing Apps,' IJSRSET 12(4):71–79.