Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
Introduction to algorithms
Constraint-directed negotiation of resource reallocations
Distributed Artificial Intelligence (Vol. 2)
Predicting tradeoffs in contract-based distributed scheduling
Predicting tradeoffs in contract-based distributed scheduling
Empirical methods for artificial intelligence
Empirical methods for artificial intelligence
Frontiers of electronic commerce
Frontiers of electronic commerce
Computationally Manageable Combinational Auctions
Management Science
Sequencing of Contract Types for Anytime Task Reallocation
AMET '98 Selected Papers from the First International Workshop on Agent Mediated Electronic Trading on Agent Mediated Electronic Commerce
Leveled Commitment Contracting among Myopic Individually Rational Agents
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Negotiation among self-interested computationally limited agents
Negotiation among self-interested computationally limited agents
The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver
IEEE Transactions on Computers
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Optimal sequencing of individually rational contracts
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Task selection problem under uncertainty as decision-making
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Autonomous Agents and Multi-Agent Systems
Agents in E-commerce: state of the art
Knowledge and Information Systems
Deliberation Levels in Theoretic-Decision Approaches for Task Allocation in Resource-Bounded Agents
Balancing Reactivity and Social Deliberation in Multi-Agent Systems, From RoboCup to Real-World Applications (selected papers from the ECAI 2000 Workshop and additional contributions)
An Adaptive Agent Society for Environmental Scanning through the Internet
PRIMA 2001 Proceedings of the 4th Pacific Rim International Workshop on Multi-Agents, Intelligent Agents: Specification, Modeling, and Applications
Distributed agents for cost-effective monitoring of critical success factors
Decision Support Systems
An Extended Multi-Agent Negotiation Protocol
Autonomous Agents and Multi-Agent Systems
On the Communication Complexity of Multilateral Trading: Extended Report
Autonomous Agents and Multi-Agent Systems
Issues in computational Vickrey auctions
International Journal of Electronic Commerce - Special issue: Intelligent agents for electronic commerce
UNCERTAIN SPATIO-TEMPORAL REASONING FOR DISTRIBUTED TRANSPORTATION SCHEDULING PROBLEM
Applied Artificial Intelligence
Making markets and democracy work: a story of incentives and computing
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
K-swaps: cooperative negotiation for solving task-allocation problems
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Simple negotiation schemes for agents with simple preferences: sufficiency, necessity and maximality
Autonomous Agents and Multi-Agent Systems
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The capability to reallocate items--e.g. tasks, securities, bandwidth slices, Mega Watt hours of electricity, and collectibles--is a key feature in automated negotiation. Especially when agents have preferences over combinations of items, this is highly nontrivial. Marginal cost based reallocation leads to an anytime algorithm where every agent's payoff increases monotonically over time. Different contract types head toward different locally optimal allocations of items, and OCSM-contracts head toward the global optimum. Reaching it can take impractically long, so it is important to trade off solution quality against negotiation time. To construct negotiation protocols that lead to good allocations quickly, we evaluated original (O), cluster (C), swap (S), and multiagent (M) contracts experimentally. O-contracts led to the highest social welfare when the ratio of agents to tasks was large, and C-contract were best when that ratio was small. O-contracts led to the largest number of contracts made. M-contracts were slower per contract, and required a significantly larger number of contracts to be tried to verify that a local optimum had been reached. S-contracts were not competitive because they restrict the search space by keeping the number of items per agent invariant. O-contracts spread the items across agents while C-contracts and M-contracts concentrated them on a few agents.