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ICML
2007
IEEE
14 years 9 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
ML
1998
ACM
220views Machine Learning» more  ML 1998»
13 years 8 months ago
Learning to Improve Coordinated Actions in Cooperative Distributed Problem-Solving Environments
Abstract. Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all...
Toshiharu Sugawara, Victor R. Lesser
IDC
2009
Springer
14 years 3 months ago
A Case Study on Availability of Sensor Data in Agent Cooperation
Abstract Multi-agent cooperation can in several cases be used in order to mitigate problems relating to task sharing within physical processes. In this paper we apply agent based s...
Christian Johansson, Fredrik Wernstedt, Paul David...
ECML
1997
Springer
14 years 1 months ago
Parallel and Distributed Search for Structure in Multivariate Time Series
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Tim Oates, Matthew D. Schmill, Paul R. Cohen
ICML
2006
IEEE
14 years 9 months ago
Relational temporal difference learning
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Nima Asgharbeygi, David J. Stracuzzi, Pat Langley