2398 search results - page 444 / 480 » On modelling agent systems with Erlang |
162
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JAIR
2011
15 years 1 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
189
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IJCAI
2001
15 years 7 months ago
2001
In the future, webs of unmanned air and space vehicles will act together to robustly perform elaborate missions in uncertain environments. We coordinate these systems by introduci...
154
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ATAL
2007
Springer
16 years 8 days ago
2007
Springer
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
178
Voted
ATAL
2007
Springer
16 years 8 days ago
2007
Springer
Planning in single-agent models like MDPs and POMDPs can be carried out by resorting to Q-value functions: a (near-) optimal Q-value function is computed in a recursive manner by ...
136
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ICRE
1996
IEEE
15 years 10 months ago
1996
IEEE
This paper presents a method that can be used for the elicitation and speci cation of requirements and high-level design. It supports stakeholder-based modeling, rapid feasibility...