Reinforcement learning: exploration–exploitation dilemma in multi-agent foraging task

Author:

Yogeswaran Mohan,Ponnambalam S. G.

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,Computer Science Applications,Information Systems,Management Information Systems

Reference17 articles.

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2. Even-Dar, E., Mansour, Y.: Convergence of optimistic and incremental $\mathcal Q$ -learning. Adv. Neural Inf. Process. Syst. 2, 1499–1506 (2002)

3. Guo, M., Liu, Y., Malec, J.: A new $\mathcal Q$ -learning algorithm based on the metropolis criterion. IEEE Trans. Syst. Man Cybern. 34(5), 2141 (2004)

4. Kareem Jaradat, M., Al-Rousan, M., Quadan, L.: Reinforcement based mobile robot navigation in dynamic environment. Robot. Comput.-Integr. Manuf. 27(1), 135–149 (2011)

5. Kearns, M., Singh, S.: Near-optimal reinforcement learning in polynomial time. Mach. Learn. 49(2), 209–232 (2002)

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