Planning for conjunctive goals
Artificial Intelligence
Planning as search: a quantitative approach
Artificial Intelligence
Reaching agreement through partial revelation of preferences
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Theory and algorithms for plan merging
Artificial Intelligence
Multi-Agent Planning as Search for a Consensus that Maximizes Social Welfare
MAAMAW '92 Selected papers from the 4th European Workshop on on Modelling Autonomous Agents in a Multi-Agent World, Artificial Social Systems
Coordinating Distributed Decision Making Using Reusable Interaction Specifications
PRIMA '00 Proceedings of the Third Pacific Rim International Workshop on Multi-Agents: Design and Applications of Intelligent Agents
Complexity of manipulating elections with few candidates
Eighteenth national conference on Artificial intelligence
Journal of Computer and System Sciences
Anyone but him: The complexity of precluding an alternative
Artificial Intelligence
Sincere-Strategy Preference-Based Approval Voting Broadly Resists Control
MFCS '08 Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science
Parameterized computational complexity of control problems in voting systems
Theoretical Computer Science
Parameterized complexity of control problems in Maximin election
Information Processing Letters
Co-ordination in artificial agent societies: social structures and its implications for autonomous problem-solving agents
Control complexity in fallback voting
CATS '10 Proceedings of the Sixteenth Symposium on Computing: the Australasian Theory - Volume 109
Hybrid voting protocols and hardness of manipulation
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Multiagent systems, and the search for appropriate foundations
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
The complexity of losing voters
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Information Systems Frontiers
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When autonomous agents attempt to coordinate action, it is often necessary that they reach some kind of consensus. Reaching consensus has traditionally been dealt with in the Distributed Artificial Intelligence literature via negotiation. Another alternative is to have agents use a voting mechanism; each agent expresses its preferences, and a group choice mechanism is used to select the result. Some choice mechanisms are better than others, and ideally we would like one that cannot, be manipulated by untruthful agents. Coordination of actions by a group of agents corresponds to a group planning process. We here introduce a new multi-agent planning technique, that makes use of a dynamic, iterative search procedure. Through a process of group constraint aggregation, agents incrementally construct a plan that brings the group to a state maximizing social welfare. At each step, agents vote about the next joint action in the group plan (i.e., what the next transition state will be in the emerging plan) Using this technique agents need not fully reveal their preferences, and the set of alternative final states need not be generated in advance of a vote. With a minor variation, the entire procedure can be made resistant to untruthful agents.