Online computation and competitive analysis
Online computation and competitive analysis
Autonomic computing: helping computers help themselves
IEEE Spectrum - They might be giants
The Vision of Autonomic Computing
Computer
UCP-Networks: A Directed Graphical Representation of Conditional Utilities
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Making Rational Decisions Using Adaptive Utility Elicitation
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A POMDP formulation of preference elicitation problems
Eighteenth national conference on Artificial intelligence
Incremental utility elicitation with minimax regret decision criterion
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Problem-focused incremental elicitation of multi-attribute tility models
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Knowledge-based acquisition of tradeoff preferences for negotiating agents
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
SLA based profit optimization in web systems
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
A Multi-Agent Systems Approach to Autonomic Computing
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
SLA based profit optimization in autonomic computing systems
Proceedings of the 2nd international conference on Service oriented computing
Regret minimizing equilibria and mechanisms for games with strict type uncertainty
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Research challenges of autonomic computing
Proceedings of the 27th international conference on Software engineering
International Journal of Human-Computer Studies
Constraint-based optimization and utility elicitation using the minimax decision criterion
Artificial Intelligence
Peer-it: Stick-on solutions for networks of things
Pervasive and Mobile Computing
Building flexible manufacturing systems based on peer-its
EURASIP Journal on Embedded Systems - Embedded System Design in Intelligent Industrial Automation
A New Self-managing Hardware Design Approach for FPGA-Based Reconfigurable Systems
ARC '08 Proceedings of the 4th international workshop on Reconfigurable Computing: Architectures, Tools and Applications
Elicitation and utilization of application-level utility functions
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
New approaches to optimization and utility elicitation in autonomic computing
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Sequential-simultaneous information elicitation in multi-agent systems
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Constraint-based optimization and utility elicitation using the minimax decision criterion
Artificial Intelligence
Regret-based reward elicitation for Markov decision processes
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Emergent consensus in decentralised systems using collaborative reinforcement learning
Self-star Properties in Complex Information Systems
Decentralized and optimal control of shared resource pools
ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special section on formal methods in pervasive computing, pervasive adaptation, and self-adaptive systems: Models and algorithms
Interactive value iteration for Markov decision processes with unknown rewards
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Decentralized resource allocation is a key problem for large-scale autonomic (or self-managing) computing systems. Motivated by a data center scenario, we explore efficient techniques for resolving resource conflicts via cooperative negotiation. Rather than computing in advance the functional dependence of each element's utility upon the amount of resource it receives, which could be prohibitively expensive, each element's utility is elicited incrementally. Such incremental utility elicitation strategies require the evaluation of only a small set of sampled utility function points, yet they find near-optimal allocations with respect to a minimax regret criterion. We describe preliminary computational experiments that illustrate the benefit of our approach.