Using Environmental Patterns to Evaluate Agent Teams Performance

The design of a rational organization composed by a team of agents is a challenging problem in domains such as collective robotics, war games and military missions. In these domains, a team is designed to confront an opponent team with technical and numerical equivalence, and aiming to conquer areas where there are scarce resources distributed in locations within a territory whose topology is unknown. In these scenarios, it is hard for the agents to do the right thing. In addition to being competitive, the task environments are unknown, partially observable and dynamic. The challenge is how to design a rational team whose members are not ideal rational agents. This work argues that one approach is to implement a suitable organizational specification that fits the task environment, according to some previously defined environmental patterns that include both domain-specific and topological characteristics. In this work, we present an experimental evaluation of these patterns' influence on the performance of teams of agents evolving on the Agents on Mars environment, a well-known agent programming testbed. The results of the evaluation show that organizational specifications that exploit this information perform better than others that don't.