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» Multi-agent systems for the real world
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ATAL
2010
Springer
13 years 8 months ago
Deception in networks of mobile sensing agents
Recent studies have investigated how a team of mobile sensors can cope with real world constraints, such as uncertainty in the reward functions, dynamically appearing and disappea...
Viliam Lisý, Roie Zivan, Katia P. Sycara, M...
ATAL
2010
Springer
13 years 8 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone
HPDC
2010
IEEE
13 years 8 months ago
Towards optimising distributed data streaming graphs using parallel streams
Modern scientific collaborations have opened up the opportunity of solving complex problems that involve multidisciplinary expertise and large-scale computational experiments. The...
Chee Sun Liew, Malcolm P. Atkinson, Jano I. van He...
GECCO
2008
Springer
186views Optimization» more  GECCO 2008»
13 years 8 months ago
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
AI
2007
Springer
13 years 7 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang