摘要翻译：
供应链形成是决定交换关系的结构和条件以实现多层次、多主体生产活动的过程。我们提出了一个简单的供应链模型，突出了两个特征：分层子任务分解和资源争用。为了分散形成过程，我们引入了一个市场价格体系，对沿着链条生产的资源进行定价。在这个系统的竞争均衡中，代理人选择关于价格的局部最优分配，结果是总体最优的。为了确定价格，我们定义了一个基于分布式、渐进拍卖和短视、非战略代理投标策略的市场协议。在存在资源争用的情况下，该协议比人工智能和多智能体系统文献中常见的贪婪协议产生了更好的解决方案。该协议通常收敛于高价值供应链，当存在竞争均衡时，通常近似于竞争均衡。然而，代理生产技术中的互补性可能导致协议浪费地将输入分配给不生产其输出的代理。随后的分解阶段将恢复损失剩余的很大一部分。
---
英文标题：
《Decentralized Supply Chain Formation: A Market Protocol and Competitive
  Equilibrium Analysis》
---
作者：
W. E. Walsh, M. P. Wellman
---
最新提交年份：
2011
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  Supply chain formation is the process of determining the structure and terms of exchange relationships to enable a multilevel, multiagent production activity. We present a simple model of supply chains, highlighting two characteristic features: hierarchical subtask decomposition, and resource contention. To decentralize the formation process, we introduce a market price system over the resources produced along the chain. In a competitive equilibrium for this system, agents choose locally optimal allocations with respect to prices, and outcomes are optimal overall. To determine prices, we define a market protocol based on distributed, progressive auctions, and myopic, non-strategic agent bidding policies. In the presence of resource contention, this protocol produces better solutions than the greedy protocols common in the artificial intelligence and multiagent systems literature. The protocol often converges to high-value supply chains, and when competitive equilibria exist, typically to approximate competitive equilibria. However, complementarities in agent production technologies can cause the protocol to wastefully allocate inputs to agents that do not produce their outputs. A subsequent decommitment phase recovers a significant fraction of the lost surplus.
---
PDF链接：
https://arxiv.org/pdf/1107.0021