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1\begin{thebibliography}{10}
2\providecommand{\url}[1]{\texttt{#1}}
3\providecommand{\urlprefix}{URL }
4\expandafter\ifx\csname urlstyle\endcsname\relax
5  \providecommand{\doi}[1]{doi:\discretionary{}{}{}#1}\else
6  \providecommand{\doi}{doi:\discretionary{}{}{}\begingroup
7  \urlstyle{rm}\Url}\fi
8\providecommand{\selectlanguage}[1]{\relax}
9\providecommand{\eprint}[2][]{\url{#2}}
10
11\bibitem{aimsunget}
12\emph{AIMSUN Getram v4.2 getting started - User's manual}. 2003.
13
14\bibitem{7_lq_methods}
15Anderson, M.~J., B.D.O.: Optimal Control - Linear Quadratic Methods.
16  \emph{Prentice Hall, Englewood Cliffs, NJ}, 1990.
17
18\bibitem{dynamic_programming}
19Bellman, R.: Dynamic programming. \emph{Princeton University Press}, 1957.
20
21\bibitem{2_int_a_in_dec}
22Ferreira, E.; Subrahmanian, E.; Manstetten, D.: Intelligent agents in
23  decentralized traffic control. \emph{Intelligent Transportation Systems},
24  2001.
25
26\bibitem{4_rmm_formalization}
27Gmytrasiewicz, P.~J.; Durfee, E.~H.: A rigorous, operational formalization of
28  recursive modeling. \emph{First International Conference on Multiagent
29  Systems}, 1995.
30
31\bibitem{5_bayes_learn}
32Nagy, I.; Nedoma, P.; Ettler, P.; aj.: O bayesovsk{\'e}m u\v{c}en{\'i}.
33  \emph{Automa}, 2002.
34
35\bibitem{1_rmm_bayes_learning}
36Ou, H.; Zhang, W.; Xu, X.: Urban traffic multi-agent system based on RMM and
37  Bayesian learning. \emph{American Control Conference}, 2002.
38
39\bibitem{17_fronta}
40P., P.; J., D.; Fl{\'i}dr: Modelling and Simultaneous Estimation of State and
41  Parameters of Traffic System. \emph{Robotics, Automation and Control}, 2008.
42
43\bibitem{learning_to_predict}
44Sutton, R.~S.: Learning to predict by the methods of temporal didffrences.
45  \emph{Machine Learning}, 1988.
46
47\bibitem{tlc_using_sarsa}
48Thorpe, T.: Vehicle traffic light controlusing sarsa. \emph{Master’s thesis,
49  Department of Computer Science, Colorado State University}, 1997.
50
51\bibitem{6_tuc_lq}
52Vaya~Dinopoulou, M.~P., Christina~Diakaki: Applications of the urban traffic
53  control strategy TUC. \emph{European Journal of Operational Research}, 2005.
54
55\bibitem{leraning_from_delayed_rewards}
56Watkins, C. J. C.~H.: Leraning from Delayed Rewards. \emph{PhD thesis, King's
57  College, Cambridge, England}, 1989.
58
59\bibitem{q_learning}
60Watkins, C. J. C.~H.; Dayan, P.: Q-leraning. \emph{Machine Learning}, 1992.
61
62\bibitem{3_i_traff_light_c}
63Wiering, M.; {Van Veenen}, J.; Vreeken, J.; aj.: Intelligent traffic light
64  control. \emph{European Research Consortium for Informatics and Mathematics},
65  2003.
66
67\bibitem{wooldridge}
68Wooldridge, M.: \emph{Multi Agent Systems}. MIT Press, Březen 2005.
69
70\end{thebibliography}
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