Abstract
We study the evolution of distributed multiagent systems under uncertainty where the autonomous agents may cooperate with each other, and/or with supervisor/operator, in order to achieve the system's objective. The cooperation is facilitated by means of information sharing among the autonomous agents and/or supervisor/operator, which has the purpose of improving the effectiveness of the autonomous agents. The evolution of cooperative systems is modeled using discrete-state, continuous-time Markov processes. To measure and quantify the degree of cooperation within such systems, we introduce the concept of coefficient of cooperation, which is obtained by minimizing the Kullback-Leibler or 1-norm distances between nonstationary probability distributions. The presented techniques are illustrated on several different types of multiagent search systems.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 39-53 |
| Number of pages | 15 |
| Journal | Military Operations Research |
| Volume | 15 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2010 |
| Externally published | Yes |
Keywords
- Coefficient of cooperation
- Cooperation
- Kullback-Leibler divergence
- Markov processes
- Multi-agent systems
ASJC Scopus subject areas
- Civil and Structural Engineering
- Mechanical Engineering
- Management Science and Operations Research