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International Conference on Computational Science, ICCS 2011 Farmer-Pest Problem: A Multidimensional Problem Domain for Comparison of Agent Learning Methods
2011
Procedia Computer Science
Learning is often utilized by multi-agent systems which can deal with complex problems by means of their decentralized approach. With a number of learning methods available, a need for their comparison arises. This paper presents initial comparison results for selected algorithms (SARSA, Naïve Bayes, C4.5 and Ripper), which are obtained based on the new multi-dimensional Farmer-Pest problem domain, which is suitable for benchmarking learning algorithms. The results show that supervised learning
doi:10.1016/j.procs.2011.04.205
fatcat:mi273mtzzbdndm55vn35422epa