Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents

Autonomous wireless agents such as unmanned aerial vehicles or mobile base stations present a great potential for deployment in next-generation wireless networks. While current literature has been mainly focused on the use of agents within robotics or software applications, we propose a novel usage model for self-organizing agents suited to wireless networks. In the proposed model, a number of agents are required to collect data from several arbitrarily located tasks. Each task represents a queue of packets that require collection and subsequent wireless transmission by the agents to a central receiver. The problem is modeled as a hedonic coalition formation game between the agents and the tasks that interact in order to form disjoint coalitions. Each formed coalition is modeled as a polling system consisting of a number of agents which move between the different tasks present in the coalition, collect and transmit the packets. Within each coalition, some agents can also take the role of a relay for improving the packet success rate of the transmission. The proposed algorithm allows the tasks and the agents to take distributed decisions to join or leave a coalition, based on the achieved benefit in terms of effective throughput, and the cost in terms of delay. As a result of these decisions, the agents and tasks structure themselves into independent disjoint coalitions which constitute a Nash-stable network partition. Moreover, the proposed algorithm allows the agents and tasks to adapt the topology to environmental changes such as the arrival/removal of tasks or the mobility of the tasks. Simulation results show how the proposed algorithm improves the performance, in terms of average player (agent or task) payoff, of at least 30.26% (for a network of 5 agents with up to 25 tasks) relatively to a scheme that allocates nearby tasks equally among agents.Comment: to appear, IEEE Transactions on Mobile Computin

Complexity of Determining Nonemptiness of the Core

Coalition formation is a key problem in automated negotiation among self-interested agents, and other multiagent applications. A coalition of agents can sometimes accomplish things that the individual agents cannot, or can do things more efficiently. However, motivating the agents to abide to a solution requires careful analysis: only some of the solutions are stable in the sense that no group of agents is motivated to break off and form a new coalition. This constraint has been studied extensively in cooperative game theory. However, the computational questions around this constraint have received less attention. When it comes to coalition formation among software agents (that represent real-world parties), these questions become increasingly explicit. In this paper we define a concise general representation for games in characteristic form that relies on superadditivity, and show that it allows for efficient checking of whether a given outcome is in the core. We then show that determining whether the core is nonempty is $\mathcal{NP}$-complete both with and without transferable utility. We demonstrate that what makes the problem hard in both cases is determining the collaborative possibilities (the set of outcomes possible for the grand coalition), by showing that if these are given, the problem becomes tractable in both cases. However, we then demonstrate that for a hybrid version of the problem, where utility transfer is possible only within the grand coalition, the problem remains $\mathcal{NP}$-complete even when the collaborative possibilities are given

The Cost of Stability in Coalitional Games

A key question in cooperative game theory is that of coalitional stability, usually captured by the notion of the \emph{core}--the set of outcomes such that no subgroup of players has an incentive to deviate. However, some coalitional games have empty cores, and any outcome in such a game is unstable. In this paper, we investigate the possibility of stabilizing a coalitional game by using external payments. We consider a scenario where an external party, which is interested in having the players work together, offers a supplemental payment to the grand coalition (or, more generally, a particular coalition structure). This payment is conditional on players not deviating from their coalition(s). The sum of this payment plus the actual gains of the coalition(s) may then be divided among the agents so as to promote stability. We define the \emph{cost of stability (CoS)} as the minimal external payment that stabilizes the game. We provide general bounds on the cost of stability in several classes of games, and explore its algorithmic properties. To develop a better intuition for the concepts we introduce, we provide a detailed algorithmic study of the cost of stability in weighted voting games, a simple but expressive class of games which can model decision-making in political bodies, and cooperation in multiagent settings. Finally, we extend our model and results to games with coalition structures.Comment: 20 pages; will be presented at SAGT'0

Coalition Formation and Combinatorial Auctions; Applications to Self-organization and Self-management in Utility Computing

In this paper we propose a two-stage protocol for resource management in a hierarchically organized cloud. The first stage exploits spatial locality for the formation of coalitions of supply agents; the second stage, a combinatorial auction, is based on a modified proxy-based clock algorithm and has two phases, a clock phase and a proxy phase. The clock phase supports price discovery; in the second phase a proxy conducts multiple rounds of a combinatorial auction for the package of services requested by each client. The protocol strikes a balance between low-cost services for cloud clients and a decent profit for the service providers. We also report the results of an empirical investigation of the combinatorial auction stage of the protocol.Comment: 14 page

Mechanism design for distributed task and resource allocation among self-interested agents in virtual organizations

The aggregate power of all resources on the Internet is enormous. The Internet can be viewed as a massive virtual organization that holds tremendous amounts of information and resources with different ownerships. However, little is known about how to run this organization efficiently. This dissertation studies the problems of distributed task and resource allocation among self-interested agents in virtual organizations. The developed solutions are not allocation mechanisms that can be imposed by a centralized designer, but decentralized interaction mechanisms that provide incentives to self-interested agents to behave cooperatively. These mechanisms also take computational tractability into consideration due to the inherent complexity of distributed task and resource allocation problems. Targeted allocation mechanisms can achieve global task allocation efficiency in a virtual organization and establish stable resource-sharing communities based on agentsâÃÂàown decisions about whether or not to behave cooperatively. This high level goal requires solving the following problems: synthetic task allocation, decentralized coalition formation and automated multiparty negotiation. For synthetic task allocation, in which each task needs to be accomplished by a virtual team composed of self-interested agents from different real organizations, my approach is to formalize the synthetic task allocation problem as an algorithmic mechanism design optimization problem. I have developed two approximation mechanisms that I prove are incentive compatible for a synthetic task allocation problem. This dissertation also develops a decentralized coalition formation mechanism, which is based on explicit negotiation among self-interested agents. Each agent makes its own decisions about whether or not to join a candidate coalition. The resulting coalitions are stable in the core in terms of coalition rationality. I have applied this mechanism to form resource sharing coalitions in computational grids and buyer coalitions in electronic markets. The developed negotiation mechanism in the decentralized coalition formation mechanism realizes automated multilateral negotiation among self-interested agents who have symmetric authority (i.e., no mediator exists and agents are peers). In combination, the decentralized allocation mechanisms presented in this dissertation lay a foundation for realizing automated resource management in open and scalable virtual organizations

Marginal contribution, reciprocity and equity in segregated groups: Bounded rationality and self-organization in social networks

We study the formation of social networks that are based on local interaction and simple rule following. Agents evaluate the profitability of link formation on the basis of the Myerson-Shapley principle that payoffs come from the marginal contribution they make to coalitions. The NP-hard problem associated with the Myerson-Shapley value is replaced by a boundedly rational 'spatially' myopic process. Agents consider payoffs from direct links with their neighbours (level 1) which can include indirect payoffs from neighbours' neighbours (level 2) and up to M-levels that are far from global. Agents dynamically break away from the neighbour to whom they make the least marginal contribution. Computational experiments show that when this self-interested process of link formation operates at level 2 neighbourhoods, agents self-organize into stable and efficient network structures that manifest reciprocity, equity and segregation reminiscent of hunter gather groups. A large literature alleges that this is incompatible with self-interested behaviour and market oriented marginality principle in the allocation of value. We conclude that it is not this valuation principle that needs to be altered to obtain segregated social networks as opposed to global components, but whether it operates at level 1 or level 2 of social neighbourhoods. Remarkably, all M>2 neighbourhood calculations for payoffs leave the efficient network structures identical to the case when M=2.