Name
Abstract | ||
|---|---|---|
Recently, an AAMAS Challenges & Visions paper identified several key components of a comprehensive trust management has been understudied by the research community [13]. We believe that we can build on recent advances in closely related research in other sub-fields of AI and multiagent systems to address some of these issues. For example, the budgeted multi-armed bandit problem involves pulling multiple arms with stochastic rewards with the goal of maximizing the total reward generated from those arms, while keeping the cost of pulling the arms beneath a given budget. We argue that multi-armed bandit algorithms can be adapted to address research issues in trust engagement and evaluation components of a comprehensive trust management approach. To support this proposition, we consider a supply-chain application, where a tree of dependent supplier agents can be considered as an arm of the online bandit problem with budget constraints. Each of the nodes in the supply chain must then solve their local bandit problem in parallel to determine which of its sub-suppliers is most trustworthy. We use new arm-selection strategies, and demonstrate how they can be gainfully applied to the trust-based decision-making in the supply chain to reduce time to production and hence improve utility by timely delivery of products. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.5555/2772879.2772900 | Autonomous Agents and Multi-Agent Systems |
Keywords | Field | DocType |
exploration-exploitation, trust management, contracting | Budget constraint,Trustworthiness,Computer science,Algorithm,Multi-agent system,Vision,Supply chain,Approaches of management | Conference |
Citations | PageRank | References |
3 | 0.41 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandip Sen | 1 | 1695 | 203.66 |
| Anton Ridgway | 2 | 3 | 0.41 |
| Michael Ripley | 3 | 3 | 0.41 |