Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning
Artificial Intelligence
Multiagent learning using a variable learning rate
Artificial Intelligence
Multi-agent policies: from centralized ones to decentralized ones
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Neuro-Dynamic Programming
The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Distributed Sensor Networks: A Multiagent Perspective
Distributed Sensor Networks: A Multiagent Perspective
Nash q-learning for general-sum stochastic games
The Journal of Machine Learning Research
Solving Distributed Constraint Optimization Problems Using Cooperative Mediation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Learning to Communicate and Act Using Hierarchical Reinforcement Learning
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
EESR '05 Proceedings of the 2005 workshop on End-to-end, sense-and-respond systems, applications and services
Learning the task allocation game
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
The Journal of Machine Learning Research
A framework for meta-level control in multi-agent systems
Autonomous Agents and Multi-Agent Systems
Generalized multiagent learning with performance bound
Autonomous Agents and Multi-Agent Systems
An Application of Automated Negotiation to Distributed Task Allocation
IAT '07 Proceedings of the 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Controlling deliberation in a Markov decision process-based agent
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Superstabilizing, fault-containing distributed combinatorial optimization
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Solving transition independent decentralized Markov decision processes
Journal of Artificial Intelligence Research
Provably bounded optimal agents
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Sequential optimality and coordination in multiagent systems
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Multiagent Meta-level Control for a Network of Weather Radars
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Decentralized monitoring of distributed anytime algorithms
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Agent-mediated multi-step optimization for resource allocation in distributed sensor networks
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Effective Variants of the Max-Sum Algorithm for Radar Coordination and Scheduling
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
The complexity of decentralized control of Markov decision processes
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Learning to cooperate via policy search
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Nash convergence of gradient dynamics in general-sum games
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
AINTEC'06 Proceedings of the Second Asian international conference on Technologies for Advanced Heterogeneous Networks
A Comprehensive Survey of Multiagent Reinforcement Learning
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems. In this paper, we argue that multiagent meta-level control is an effective way to determine when this adaptation process should be done and how much effort should be invested in adaptation as opposed to continuing with the current action plan. We use a reinforcement learning based local optimization algorithm within each agent to learn multiagent meta-level control agent policies in a decentralized fashion. These policies will allow each agent to adapt to changes in environmental conditions while reorganizing the underlying multiagent network when needed. We then augment the agent with a heuristic rule-based algorithm that uses information provided by the reinforcement learning algorithm in order to resolve conflicts among agent policies from a local perspective at both learning and execution stages. We evaluate this mechanism in the context of a multiagent tornado tracking application called NetRads. Empirical results show that adaptive multiagent meta-level control significantly improves the performance of the tornado tracking network for a variety of weather scenarios.