Maintaining shared belief in a large multiagent team

Decision and Control, …, 2005

This paper considers the problem of cooperative search and task response in a heterogeneous team of unmanned aerial vehicles (UAVs) with limited communication. The UAVs are engaged in a mission to search and verifiably destroy targets in an uncertain environment. The UAVs do not have access to centralized information, and each UAV makes its decisions based on subjective information obtained through observation and communication with other UAVs. We present a strategy for information sharing and fusion, and study the impact of this strategy's parameters on the performance of the UAV team.

2010

Members of large, heterogeneous teams often need to interact with different kinds of teammates to accomplish their tasks, teammates with dramatically different capabilities to their own. While the role of humans in teams has progressively decreased with the deployment of increasingly intelligent systems, they still have a major role to play.

Knowledge and Information Systems, 2016

This paper introduces an approach for sharing beliefs in collaborative multi-agent application domains where some agents can be more credible than others. In this context, we propose a formalization where every agent has its own partial order among its peers representing the credibility the agent assigns to its informants; each agent will also have a belief base where each sentence is attached with an agent identifier which represents the credibility of that sentence. We define four different forwarding criteria for computing the credibility information for a belief to be forwarded, and for determining how the receiver should handle the incoming information; the proposal considers both the sender's and the receiver's points of view with respect to the credibility of the source of the information.

2008

Abstract Effective communication among agents in large teams is crucial because the members share a common goal but only have a partial views of the environment. Information sharing is difficult in a large team because, a team member may have a piece of valuable information but not know who needs the information, since it is infeasible to know what each other agent is doing.

2010

Abstract Large heterogeneous teams will often be in situations where sensor data that is uncertain and conflicting is shared across a peer-to-peer network. Not every team member will have direct access to sensors and team members will be influenced mostly by teammates with whom they communicate directly. In this paper, we investigate the dynamics and emergent behaviors of a large team sharing beliefs to reach conclusions about the world.

2004

Abstract Effective communication among agents in large teams is crucial because the members share a common goal but only have a partial views of the environment. Information sharing is difficult in a large team because, a team member may have a piece of valuable information but not know who needs the information, since it is infeasible to know what each other agent is doing.

Springer Optimization and Its Applications, 2010

Individuals in large, heterogeneous teams will commonly produce sensor data that is likely useful to some other members of the team, but it is not precisely known to whom the information is useful. Some recent work has shown that randomly propagating the information performed surprisingly well, compared to infeasible optimal approaches. This chapter extends that work by looking at how the relative performance of random information passing algorithms scales with the size of the team. Additionally, the chapter looks at how random information passing performs when sensor data is noisy, so that individuals need multiple pieces of data to reach a conclusion, and the underlying situation is dynamic, so individuals need new information over time. Results show that random information passing is broadly effective, although relative performance is lower in some situations.

Decision Support Systems, 2006

Proactive information sharing is a challenging issue faced by intelligence agencies in effectively making critical decisions under time pressure in areas related to homeland security. Motivated by psychological studies on human teams, a team-oriented agent architecture, Collaborative Agents for Simulating Teamwork (CAST), was implemented to allow agents in a team to anticipate the information needs of teammates and help them with their information needs proactively and effectively. In this paper, we extend CAST with a decision-making module. Through two sets of experiments in a simulated battlefield, we evaluate the effectiveness of the decision-theoretic proactive communication strategy in improving team performance, and the effectiveness of information fusion as an approach to alleviating the information overload problem faced by distributed decision makers. D

Proceedings of the 26th Australasian Computer Science Conference Volume 16, 2003

In this paper, we present several general policies for deciding when to share probabilistic beliefs between agents for distributed monitoring. In order to evaluate these policies, we have formulated an application in network intrusion detection as a multi-agent monitoring problem. We have evaluated our policies based on packet trace data from a real network. Based on this evaluation, we have demonstrated that our policies can reduce both the delay and communication overhead required to detect network intrusions. Although we have focused on network intrusion detection as an application, we contend that our policies can generally be applied to domains that use a probabilistic model for evaluating hypotheses, and have a method for combining beliefs from multiple agents.

Dss, 2005

Proactive information sharing is a challenging issue faced by intelligence agencies in effectively making critical decisions under time pressure in areas related to homeland security. Motivated by psychological studies on human teams , a team-oriented agent architecture --CAST (Collaborative Agents for Simulating Teamwork), was implemented to allow agents in a team to anticipate the information needs of teammates and help them with their information needs proactively, effectively, and timely. In this paper, we extend CAST with a decision-making module . Through two sets of experiments in a simulated battlefield, we evaluate the effectiveness of the decision theoretic proactive communication strategy in improving team performance, and the effectiveness of information fusion as an approach to alleviating the information overload problem faced by distributed decision makers.