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AGENTS
2001
Springer
13 years 12 months ago
Hierarchical multi-agent reinforcement learning
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 8 months ago
Supply chain management sales using XCSR
The Trading Agent Competition in its category Supply Chain Management (TAC SCM) is an international forum where teams construct agents that control a computer assembly company in ...
María A. Franco, Ivette C. Martínez,...
STOC
2004
ACM
150views Algorithms» more  STOC 2004»
14 years 7 months ago
Typical properties of winners and losers in discrete optimization
We present a probabilistic analysis for a large class of combinatorial optimization problems containing, e.g., all binary optimization problems defined by linear constraints and a...
René Beier, Berthold Vöcking
MAGS
2008
104views more  MAGS 2008»
13 years 7 months ago
Retractable contract network for empowerment in workforce scheduling
This paper is about business modelling and negotiation protocol design in distributed scheduling, where individual agents have individual (potentially conflicting) interests. It i...
Edward P. K. Tsang, Timothy Gosling, Botond Virgin...
AAAI
2008
13 years 9 months ago
Resource Constrained Distributed Constraint Optimization with Virtual Variables
Cooperative problem solving with resource constraints are important in practical multi-agent systems. Resource constraints are necessary to handle practical problems including dis...
Toshihiro Matsui, Hiroshi Matsuo, Marius Silaghi, ...