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» Modelling Uncertainty in Agent Programming
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151
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ATAL
2007
Springer
15 years 8 months ago
Aborting tasks in BDI agents
Intelligent agents that are intended to work in dynamic environments must be able to gracefully handle unsuccessful tasks and plans. In addition, such agents should be able to mak...
John Thangarajah, James Harland, David N. Morley, ...
120
Voted
FOCS
2005
IEEE
15 years 8 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
DAGSTUHL
2007
15 years 4 months ago
Sampling-based Approximation Algorithms for Multi-stage Stochastic Optimization
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Chaitanya Swamy, David B. Shmoys
110
Voted
WINE
2009
Springer
121views Economy» more  WINE 2009»
15 years 9 months ago
Gaming Dynamic Parimutuel Markets
We study the strategic behavior of risk-neutral non-myopic agents in Dynamic Parimutuel Markets (DPM). In a DPM, agents buy or sell shares of contracts, whose future payoff in a p...
Qianya Lin, Yiling Chen
111
Voted
ATAL
2003
Springer
15 years 7 months ago
Coalition formation through motivation and trust
Cooperation is the fundamental underpinning of multi-agent systems, allowing agents to interact to achieve their goals. Where agents are self-interested, or potentially unreliable...
Nathan Griffiths, Michael Luck