How HiveMind Optimizes LLM Multi‑Agent Trading Systems via Contribution‑Guided Online Prompts

The HiveMind framework introduces a contribution‑guided online prompt optimization (CG‑OPO) that quantifies each LLM‑driven agent’s impact with Shapley values and uses a DAG‑Shapley algorithm to efficiently attribute credit, enabling real‑time adaptive optimization of multi‑agent stock‑trading systems and achieving superior returns with far fewer LLM calls.

DAG-ShapleyFinancial TradingLLM

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How HiveMind Optimizes LLM Multi‑Agent Trading Systems via Contribution‑Guided Online Prompts

Model Perspective

Sep 24, 2024 · Fundamentals

How to Fairly Split Group Project Scores Using Shapley Value and LOTB

This article explains cooperative game theory concepts—Last‑On‑The‑Bus Value and Shapley Value—and demonstrates how they can be used to fairly allocate scores among group project members by evaluating each participant’s marginal contributions across all possible joining orders.

Shapley valuecooperative game theoryfair allocation

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How to Fairly Split Group Project Scores Using Shapley Value and LOTB

Model Perspective

Mar 4, 2023 · Artificial Intelligence

How Shapley Values Reveal Fair Profit Splits and Explain Machine Learning Models

This article introduces the Shapley value concept, its fairness axioms, demonstrates its use in a profit‑allocation problem and in interpreting machine‑learning models with SHAP, and provides complete Python implementations for both cases.

Game TheoryPythonSHAP

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How Shapley Values Reveal Fair Profit Splits and Explain Machine Learning Models

Alimama Tech

Aug 3, 2022 · Artificial Intelligence

CausalMTA: Unbiased Multi‑Touch Attribution via Causal Inference

CausalMTA introduces a causal‑inference‑based multi‑touch attribution framework that eliminates static user‑attribute bias through variational recurrent auto‑encoder re‑weighting and dynamic preference bias via a gradient‑reversal‑layer‑augmented RNN, producing an unbiased conversion predictor whose Shapley‑value credits outperform existing methods on synthetic, Criteo, and Alibaba datasets.

Bias CorrectionShapley valuecausal inference

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CausalMTA: Unbiased Multi‑Touch Attribution via Causal Inference