Time Does Not Always Buy Quality in Co-evolutionary Learning

1. Shannon, C.: Programming a computer for playing chess. Philosophical Magazine 41(4), 265–275 (1950)

   MathSciNet  Google Scholar 

2. Samuel, A.: Some Studies in Machine Learning Using the Game of Checkers. IBM Journal of Research and Development 3, 210–229 (1959)

   Article  Google Scholar 

3. Hsu, F.-H.: Behind Deep Blue: Building the Computer that Defeated the World Chess Champion. Princeton University Press, Princeton (2002)

   MATH  Google Scholar 

4. Schaeffer, J., Bjoernsson, Y., Burch, N., Kishimoto, A., Mueller, M., Lake, R., Lu, P., Sutphen, S.: Solving Checkers. In: International Joint Conference on Artificial Intelligence (2005)

   Google Scholar 

5. Kalles, D., Kanellopoulos, P.: On Verifying Game Design and Playing Strategies using Reinforcement Learning. In: ACM Symposium on Applied Computing, special track on Artificial Intelligence and Computation Logic, Las Vegas (2001)

   Google Scholar 

6. Sutton, R.: Learning to Predict by the Methods of Temporal Differences. Machine Learning 3(1), 9–44 (1988)

   Google Scholar 

7. Sutton, R., Barto, A.: Reinforcement Learning - An Introduction. MIT Press, Cambridge (1988)

   Google Scholar 

8. Tesauro, G.: Temporal Difference Learning and TD-Gammon. Communications of the ACM 38(3), 58–68 (1995)

   Article  Google Scholar 

9. Littman, M.L.: Markov Games as a Framework for Multi-Agent Reinforcement Learning. In: 11th International Conference on Machine Learning, San Francisco, pp. 157–163 (1994)

   Google Scholar 

10. Kalles, D., Ntoutsi, E.: Interactive Verification of Game Design and Playing Strategies. In: IEEE International Conference on Tools with Artificial Intelligence, Washington D.C. (2002)

    Google Scholar 

11. Kalles, D.: Player co-modelling in a strategy board game: discovering how to play fast. Cybernetics and Systems 39(1), 1–18 (2008)

    Article  MATH  Google Scholar 

12. Kalles, D., Kanellopoulos, P.: A Minimax Tutor for Learning to Play a Board Game. In: 18th European Conference on Artificial Intelligence, workshop on Artificial Intelligence in Games, Patras, Greece, pp. 10–14 (2008)

    Google Scholar 

13. Nicolescu, M.N., Matarić, M.J.: Natural methods for robot task learning: Instructive demonstrations, generalization and practice. In: 2nd International Conference on Autonomous Agents and Multi-Agent Systems, Melbourne, pp. 241–248 (2003)

    Google Scholar 

14. Kaplan, F., Oudeyer, P.-Y., Kubinyi, E., Miklosi, A.: Robotic Clicker Training. Robotics and Autonomous Systems 38(3–4), 197–206 (2002)

    Article  Google Scholar 

15. Kalles, D.: Measuring Expert Impact on Learning how to Play a Board Game. In: 4th IFIP Conference on Artificial Intelligence Applications and Innovations, Athens, Greece (2007)

    Google Scholar 

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