To Share or not to Share? The Single Agent in a Team Decision Problem

This paper defines the "Single Agent in a Team Decision" (SATD) problem. SATD differs from prior multi-agent communication problems in the assumptions it makes about teammates' knowledge of each other's plans and possible observations. The paper proposes a novel integrated logical-decision-theoretic approach to solving SATD problems, called MDP-PRT. Evaluation of MDP-PRT shows that it outperforms a previously proposed communication mechanism that did not consider the timing of communication and compares favorably with a coordinated Dec-POMDP solution that uses knowledge about all possible observations.Engineering and Applied Science

Applying MDP Approaches for Estimating Outcome of Interaction in Collaborative Human-Computer Settings

This paper investigates the problem of determining when a computer agent should interrupt a person with whom it is working collaboratively as part of a distributed, multi-agent team, which is operating in environments in which conditions may be rapidly changing, actions occur at a fast pace, and decisions must be made within tightly constrained time frames. An interruption would enable the agent to obtain information useful for performing its role in the team task, but the person will incur a cost in responding. The paper presents a formalization of interruptions as multi-agent decision making. It defines a novel, efficient approximation method that decouples the multi-agent decision model into separate MDPs, thereby overcoming the complexity of finding optimal solutions of the Dec-POMDP model. For single-shot situations, the separate outcomes can be combined to give an exact value for the interruption. In more general settings, the closeness of the approximation to the optimal solution depends on the structure of the problem. The paper describes domain specific heuristic functions that improve the efficiency of the approximation further for a specific application.Engineering and Applied Science

TOKEN-BASED APPROACH FOR SCALABLE TEAMCOORDINATION

To form a cooperative multiagent team, autonomous agents are required to harmonize activities and make the best use of exclusive resources to achieve their common goal. In addition, to handle uncertainty and quickly respond to external environmental events, they should share knowledge and sensor in formation. Unlike small team coordination, agents in scalable team must limit the amount of their communications while maximizing team performance. Communication decisions are critical to scalable-team coordination because agents should target their communications, but these decisions cannot be supported by a precise model or by complete team knowledge.The hypothesis of my thesis is: local routing of tokens encapsulating discrete elements of control, based only on decentralized local probability decision models, will lead to efficient scalable coordination with several hundreds of agents. In my research, coordination controls including all domain knowledge, tasks and exclusive resources are encapsulated into tokens. By passing tokens around, agents transfer team controls encapsulated in the tokens. The team benefits when a token is passed to an agent who can make use of it, but communications incur costs. Hence, no single agent has sole responsible over any shared decision. The key problem lies in how agents make the correct decisions to target communications and pass tokens so that they will potentially benefit the team most when considering communication costs.My research on token-based coordination algorithm starts from the investigation of random walk of token movement. I found a little increase of the probabilities that agents make the right decision to pass a token, the overall efficiency of the token movement could be greatly enhanced. Moreover, if token movements are modeled as a Markov chain, I found that the efficiency of passing tokens could be significantly varied based on different network topologies.My token-based algorithm starts at the investigation of each single decision theoretic agents. Although under the uncertainties that exist in large multiagent teams, agents cannot act optimal, it is still feasible to build a probability model for each agents to rationally pass tokens. Specifically, this decision only allow agent to pass tokens over an associate network where only a few of team members are considered as token receiver.My proposed algorithm will build each agent's individual decision model based on all of its previously received tokens. This model will not require the complete knowledge of the team. The key idea is that I will make use of the domain relationships between pairs of coordination controls. Previously received tokens will help the receiver to infer whether the sender could benefit the team if a related token is received. Therefore, each token is used to improve the routing of other tokens, leading to a dramatic performance improvement when more tokens are added. By exploring the relationships between different types of coordination controls, an integrated coordination algorithm will be built, and an improvement of one aspect of coordination will enhance the performance of the others

Effort Provision and Communication in Teams Competing over the Commons

Schott et al. (2007) have shown that the “tragedy of the commons” can be overcome when individuals share their output equally in groups of optimal size and there is no communication. In this paper we investigate the impact of introducing communication in groups that may or may not be linked to output sharing groups. Communication reduces shirking, increases aggregate effort and reduces aggregate rents, but only when communication groups and output-sharing groups are linked. The effect is stronger for fixed groups (partners treatment) than for randomly reassigned groups (strangers treatment). Performance is not distinguishable from the no-communication treatments when communication is permitted but subjects share output within groups different from the groups within which they communicate. Communication also tends to enhance the negative effect of the partnered group assignment on the equality of individual payoffs. We use detailed content analysis to evaluate the impact of communication messages on behavior across treatments.common pool resources; communication; coordination; cooperation; free-riding; behavior in teams; partners and strangers; experiments

Collective responsibility and collective obligations without collective moral agents

It is commonplace to attribute obligations to φ or blameworthiness for φ-ing to groups even when no member has an obligation to φ or is individually blameworthy for not φ-ing. Such non-distributive attributions can seem problematic in cases where the group is not a moral agent in its own right. In response, it has been argued both that non-agential groups can have the capabilities requisite to have obligations of their own, and that group obligations can be understood in terms of moral demands on individual group members. It has also been suggested that members of groups can share responsibility for an outcome in virtue of being causally or socially connected to that outcome. This paper discusses the agency problem and argues that the most promising attempts at solutions understand group obligations and blameworthiness as grounded in demands on individual agents