An integrated token-based algorithm for scalable coordination

Abstract

Efficient coordination among large numbers of heterogeneous agents promises to revolutionize the way in which some complex tasks, such as responding to urban disasters can be performed. However, state of the art coordination algorithms are not capable of achieving efficient and effective coordination when a team is very large. Building on recent successful token-based algorithms for task allocation and information sharing, we have developed an integrated and efficient approach to effective coordination of large scale teams. We use tokens to encapsulate anything that needs to be shared by the team, including information, tasks and resources. The tokens are efficiently routed through the team via the use of local decision theoretic models. Each token is used to improve the routing of other tokens leading to a dramatic performance improvement when the algorithms work together. We present results from an implementation of this approach which demonstrates its ability to coordinate large teams.

Analyzing the Theoretical Performance of Information Sharing

“…Approaches such as STEAM [14] and matchmakers [8] share knowledge about information requirements in order to reason about where to direct information. Gossip algorithms [2] and token passing algorithms [17,15] use randomized local policies to share information and are thus particularly suited to large scale problems. To address the expense of synchronizing beliefs over teams, several techniques have been developed in conjunction with decentralized Bayesian filtering techniques, including channel managers [1] and query-based particle filters [11].…”

Scalable Coordination Mechanism to Maintain Throughput of Dynamic Multiagent Networks

“…In JIT, a machine exchanges tokens (Kanban cards) between its adjacent machines to control flows and amounts of WIP in the system. In fact, JIT and its extensions such as CONWIP are instances of token-based coordination (Wagner et al, 2003, Xu et al, 2005, Moyaux et al, 2003 and widely used in manufacturing and other related fields. However, because of their simplicity, they cannot correspond smoothly to changes of the environment such as demand fluctuations and machine failures.…”

Towards flexible coordination of human-agent teams

“…Current versions of Machinetta include state-of-the-art algorithms for plan instantiation [11], role allocation [25], information sharing [24], task deconfliction [11], and adjustable autonomy [17]. Key algorithms, including role allocation, resource allocation, information sharing and plan instantiation are based on the use of tokens which are "pushed" onto the network and routed to where they are required by the proxies.…”

“…Key algorithms, including role allocation, resource allocation, information sharing and plan instantiation are based on the use of tokens which are "pushed" onto the network and routed to where they are required by the proxies. For example, the role allocation algorithm, explained here [25], represents each role to be allocated with a token and pushes the tokens around the network until a sufficiently capable and available team member is found to execute the role. The implementation of the coordination algorithms uses the abstraction of a simple mobile agent to implement the tokens, leading to robust and efficient software.…”