Market-based control: a paradigm for distributed resource allocation
Market-based control: a paradigm for distributed resource allocation
k-order additive discrete fuzzy measures and their representation
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
Entropy and self-organization in multi-agent systems
Proceedings of the fifth international conference on Autonomous agents
Strategic negotiation in multiagent environments
Strategic negotiation in multiagent environments
Introduction to Multiagent Systems
Introduction to Multiagent Systems
On the Communication Complexity of Multilateral Trading
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
The complexity of contract negotiation
Artificial Intelligence
Computational-Mechanism Design: A Call to Arms
IEEE Intelligent Systems
Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition (Intelligent Robotics and Autonomous Agents)
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
Allocating goods on a graph to eliminate envy
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Extremal behaviour in multiagent contract negotiation
Journal of Artificial Intelligence Research
Negotiating socially optimal allocations of resources
Journal of Artificial Intelligence Research
Resource allocation among agents with MDP-induced preferences
Journal of Artificial Intelligence Research
Hi-index | 0.00 |
Distributed allocation mechanisms rely on the agents' autonomous (and supposedly rational) behaviour: states evolve as a result of agents contracting deals and exchanging resources. It is no surprise that restrictions on potential deals also restrict the reachability of some desirable states, for instance states where goods are efficiently allocated. In particular topological restrictions make any attempt to guarantee asymptotic convergence to an optimal allocation impossible in most cases. In this paper, we concentrate on the dynamics of such systems; more precisely we study the trajectories of goods in such iterative reallocative processes. Our first contribution is to propose an upper bound on the length of the trajectories of goods, when agent utility functions are modular. The second innovative aspect of the paper is then to discuss how this affects, on average, the quality of the states that are reached. Finally, a preliminary study of the non-modular case is proposed, examining how synergetic effects between items can affect their trajectories.