A new heuristic for the multi-depot vehicle routing problem that improves upon best-known solutions
American Journal of Mathematical and Management Sciences - Special issue: vehicle routing 2000: advances in time windows, optimality, fast bounds, & multi-depot routing
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Multiagent learning using a variable learning rate
Artificial Intelligence
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Solving Combinatorial Auctions Using Stochastic Local Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Contract Type Sequencing for Reallocative Negotiation
ICDCS '00 Proceedings of the The 20th International Conference on Distributed Computing Systems ( ICDCS 2000)
Combinatorial Auctions: A Survey
INFORMS Journal on Computing
Collaborative execution of exploration and tracking using move value estimation for robot teams (mvert)
On Heuristics for Solving Winner Determination Problem in Combinatorial Auctions
Journal of Heuristics
Statistical Shape Analysis: Clustering, Learning, and Testing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Monte Carlo Statistical Methods (Springer Texts in Statistics)
Network+ Study Guide, 4th Edition
Network+ Study Guide, 4th Edition
Generalizing Swendsen-Wang to Sampling Arbitrary Posterior Probabilities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combinatorial Auctions
A constraint optimization framework for fractured robot teams
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Online Optimization for Latency Assignment in Distributed Real-Time Systems
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
The power of sequential single-item auctions for agent coordination
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Sequential bundle-bid single-sale auction algorithms for decentralized control
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Consensus-based decentralized auctions for robusttask allocation
IEEE Transactions on Robotics
K-swaps: cooperative negotiation for solving task-allocation problems
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Dynamic and distributed frequency assignment for energy and latency constrained MP-SoC
Proceedings of the Conference on Design, Automation and Test in Europe
Robotic Urban Search and Rescue: A Survey from the Control Perspective
Journal of Intelligent and Robotic Systems
An Efficient Stochastic Clustering Auction for Heterogeneous Robotic Collaborative Teams
Journal of Intelligent and Robotic Systems
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This article considers the problem of optimal task allocation for heterogeneous teams, for example, teams of heterogeneous robots or human-robot teams. It is well-known that this problem is NP-hard and hence computationally feasible approaches must develop an approximate solution. Here, we propose a solution via a Stochastic Clustering Auction (SCA) that uses a Markov chain search process along with simulated annealing. This is the first stochastic auction method used in conjunction with global optimization. It is based on stochastic transfer and swap moves between the clusters of tasks assigned to the various robots and considers not only downhill movements, but also uphill movements, which can avoid local minima. A novel feature of this algorithm is that, by tuning the annealing suite and turning the uphill movements on and off, the global team performance after algorithm convergence can slide in the region between the global optimal performance and the performance associated with a random allocation. Extensive numerical experiments are used to evaluate the performance of SCA in terms of costs and computational and communication requirements. For centralized auctioning, the SCA algorithm is compared to fast greedy auction algorithms. Distributed auctioning is then compared with centralized SCA.