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AAAI
2008
13 years 10 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
ATAL
2005
Springer
14 years 1 months ago
Modeling task allocation using a decision theoretic model
Mediation is the process of decomposing a task into subtasks, finding agents suitable for these subtasks and negotiating with agents to obtain commitments to execute these subtas...
Sherief Abdallah, Victor R. Lesser
ATAL
2008
Springer
13 years 9 months ago
Artificial agents learning human fairness
Recent advances in technology allow multi-agent systems to be deployed in cooperation with or as a service for humans. Typically, those systems are designed assuming individually ...
Steven de Jong, Karl Tuyls, Katja Verbeeck
ATAL
2005
Springer
14 years 1 months ago
Modeling opponent decision in repeated one-shot negotiations
In many negotiation and bargaining scenarios, a particular agent may need to interact repeatedly with another agent. Typically, these interactions take place under incomplete info...
Sabyasachi Saha, Anish Biswas, Sandip Sen
AAAI
2006
13 years 9 months ago
Learning of Agents with Limited Resources
In this paper we present our preliminary investigation of rational agents who can learn from their experience. We claim that such agents need to combine at least three attributes
Slawomir Nowaczyk