Deliberation scheduling for problem solving in time-constrained environments
Artificial Intelligence
Emergent coordination through the use of cooperative state-changing rules
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Divide and conquer in multi-agent planning
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Intelligent planning: a decomposition and abstraction based approach
Intelligent planning: a decomposition and abstraction based approach
Top-down search for coordinating the hierarchical plans of multiple agents
Proceedings of the third annual conference on Autonomous Agents
Evaluating new options in the context of existing plans
Artificial Intelligence
Efficient Mechanisms for Multiagent Plan Merging
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
A distributed framework for solving the Multiagent Plan Coordination Problem
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
An efficient algorithm for multiagent plan coordination
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Coordinating Self-interested Planning Agents
Autonomous Agents and Multi-Agent Systems
On the benefits of exploiting underlying goals in argument-based negotiation
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Abstract reasoning for planning and coordination
Journal of Artificial Intelligence Research
A formal analysis of interest-based negotiation
Annals of Mathematics and Artificial Intelligence
Introduction to planning in multiagent systems
Multiagent and Grid Systems - Planning in multiagent systems
Coordination by design and the price of autonomy
Autonomous Agents and Multi-Agent Systems
On the benefits of exploiting hierarchical goals in bilateral automated negotiation
ArgMAS'07 Proceedings of the 4th international conference on Argumentation in multi-agent systems
Computationally Effective Reasoning About Goal Interactions
Journal of Automated Reasoning
Complexity of task coordination for non cooperative planning agents
CEEMAS'05 Proceedings of the 4th international Central and Eastern European conference on Multi-Agent Systems and Applications
µ-SATPLAN: Multi-agent planning as satisfiability
Knowledge-Based Systems
Framework and complexity results for coordinating non-cooperative planning agents
MATES'06 Proceedings of the 4th German conference on Multiagent System Technologies
Failing believably: toward drama management with autonomous actors in interactive narratives
TIDSE'06 Proceedings of the Third international conference on Technologies for Interactive Digital Storytelling and Entertainment
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It is critical for agents in a multiagent environment to avoid interfering with each other when carrying out their tasks. However, to avoid execution inefficiencies, they also should capitalize on cooperative opportunities. In state oriented domains [14], identifying overlapping effects between agents' plans enables some agents to leave some tasks to others, thereby reducing the cost of execution and improving the overall efficiency of the multiagent system. This is what we term synergy. In this paper, we define criteria for finding a certain type of synergy involving agents with overlapping goals. We also develop algorithms for discovering this synergy between planning agents that exploit hierarchical plan representations. Our results show that our approach not only can reduce the costs of finding synergies compared to non-hierarchical strategies, but can also find synergies that might otherwise be missed.