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» Agent Compromises in Distributed Problem Solving
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ICML
2007
IEEE
14 years 8 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
IJCAI
2003
13 years 8 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
ATAL
2005
Springer
14 years 27 days ago
Preprocessing techniques for accelerating the DCOP algorithm ADOPT
Methods for solving Distributed Constraint Optimization Problems (DCOP) have emerged as key techniques for distributed reasoning. Yet, their application faces significant hurdles...
Syed Muhammad Ali, Sven Koenig, Milind Tambe
ATAL
2006
Springer
13 years 11 months ago
On the complexity of practical ATL model checking
We investigate the computational complexity of reasoning about multi-agent systems using the cooperation logic ATL of Alur, Henzinger, and Kupferman. It is known that satisfiabili...
Wiebe van der Hoek, Alessio Lomuscio, Michael Wool...
ATAL
2009
Springer
14 years 1 months ago
From DPS to MAS to ...: continuing the trends
The most important and interesting of the computing challenges we are facing are those that involve the problems and opportunities afforded by massive decentralization and disinte...
Michael N. Huhns