Developing Incentive Compatible Attribution Engines for Social Advertising using Game Theoretic Autonomous Agents and Distributed Transaction Pipelines - Harrison Sterling (Computational Intelligence Systems, 2026)
The efficacy of social advertising infrastructures is increasingly compromised by the lack of transparent, fair, and incentive-compatible attribution mechanisms. Modern digital advertising relies on complex multi-touch journeys where multiple stakeholders—including influencers, platform algorithms, and third-party affiliates—contribute to a final conversion event. However, existing attribution engines often utilize simplistic heuristics like last-click or first-touch, which fail to capture the true marginal contribution of each participant and encourage adversarial behaviors such as attribution fraud and strategic data withholding. This paper proposes a novel architectural framework for attribution engines that synergizes game-theoretic autonomous agents with distributed transaction pipelines to achieve incentive compatibility. By treating the attribution problem as a cooperative game, we utilize Shapley value-inspired logic to distribute rewards based on the coalitional contribution of every touchpoint in the user journey. The system is implemented through a high-throughput distributed pipeline that ensures transactional integrity and causal consistency across heterogeneous social platforms. We explore the structural trade-offs between computational overhead and attribution precision, emphasizing the necessity of hardware-aware orchestration for real-time incentive calculation. Furthermore, the research addresses critical socio-technical dimensions, including the governance of autonomous agents, the sustainability of large-scale distributed ledgers, and the ethical imperatives of algorithmic fairness in decentralized marketplaces. By aligning individual incentives with systemic efficiency, this framework provides a robust blueprint for a more resilient and transparent social advertising ecosystem that is resistant to manipulation and capable of fostering long-term trust among diverse stakeholders.