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128
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IJAR
2006
89views more  IJAR 2006»
15 years 3 months ago
Learning probabilistic decision graphs
Probabilistic decision graphs (PDGs) are a representation language for probability distributions based on binary decision diagrams. PDGs can encode (context-specific) independence...
Manfred Jaeger, Jens D. Nielsen, Tomi Silander
128
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ML
1998
ACM
117views Machine Learning» more  ML 1998»
15 years 3 months ago
Learning Team Strategies: Soccer Case Studies
We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy, but may behave di erently due to position-dependent inputs. All...
Rafal Salustowicz, Marco Wiering, Jürgen Schm...
113
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GECCO
2005
Springer
174views Optimization» more  GECCO 2005»
15 years 9 months ago
Emergence of communication in competitive multi-agent systems: a pareto multi-objective approach
In this paper we investigate the emergence of communication in competitive multi-agent systems. A competitive environment is created with two teams of agents competing in an explo...
Michelle McPartland, Stefano Nolfi, Hussein A. Abb...
121
Voted
IJCNN
2006
IEEE
15 years 9 months ago
Dynamic Hyperparameter Scaling Method for LVQ Algorithms
— We propose a new annealing method for the hyperparameters of several recent Learning Vector Quantization algorithms. We first analyze the relationship between values assigned ...
Sambu Seo, Klaus Obermayer
ATAL
2008
Springer
15 years 5 months ago
Efficient multi-agent reinforcement learning through automated supervision
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser