K. L. Myers, Towards a framework for continuous planning and execution, Proc. of the AAAI Fall Symposium on Distributed Continual Planning, 1998.

C. Mcgann, F. Py, K. Rajan, H. Thomas, R. Henthorn et al., A deliberative architecture for AUV control, 2008 IEEE International Conference on Robotics and Automation, 2008.
DOI : 10.1109/ROBOT.2008.4543343

J. Pinto, J. Sousa, F. Py, and K. Rajan, Experiments with Deliberative Planning on Autonomous Underwater Vehicles, In: IROS Workshop on Robotics for Environmental Modeling, 2012.

S. Jimènez, F. Fernández, and D. Borrajo, INTEGRATING PLANNING, EXECUTION, AND LEARNING TO IMPROVE PLAN EXECUTION, Computational Intelligence, vol.24, issue.1, pp.1-36, 2013.
DOI : 10.1111/j.1467-8640.2012.00447.x

M. Shah, T. Mccluskey, P. Gregory, and F. Jimoh, Modelling Road Traffic Incident Management Problems for Automated Planning, IFAC Proceedings Volumes, vol.45, issue.24, pp.138-143, 2012.
DOI : 10.3182/20120912-3-BG-2031.00075

URL : http://eprints.hud.ac.uk/14258/1/ifacconf.pdf

F. Jimoh, L. Chrpa, P. Gregory, and T. Mccluskey, Enabling autonomic properties in road transport system, The 30th Workshop of the UK Planning And Scheduling Special Interest Group, 2012.

D. A. Roozemond, Using intelligent agents for pro-active, real-time urban intersection control, European Journal of Operational Research, vol.131, issue.2, pp.293-301, 2001.
DOI : 10.1016/S0377-2217(00)00129-6

D. Oliveira, D. Bazzan, and A. L. , Multiagent Learning on Traffic Lights Control, In: MultiAgent Systems for Traffic and Transportation Engineering, pp.307-322, 2009.
DOI : 10.4018/978-1-60566-226-8.ch015

Z. Yang, X. Chen, Y. Tang, and J. Sun, Intelligent cooperation control of urban traffic networks, Proceedings of the International Conference on Machine Learning and Cybernetics, pp.1482-1486, 2005.

A. L. Bazzan, A Distributed Approach for Coordination of Traffic Signal Agents, Autonomous Agents and Multi-Agent Systems, vol.2, issue.6, pp.131-164, 2005.
DOI : 10.1007/s10458-004-6975-9

I. Dusparic and V. Cahill, Autonomic multi-policy optimization in pervasive systems, ACM Transactions on Autonomous and Adaptive Systems, vol.7, issue.1, pp.1-25, 2012.
DOI : 10.1145/2168260.2168271

A. Gerevini, A. Saetti, and I. Serina, An approach to temporal planning and scheduling in domains with predictable exogenous events, Journal of Artificial Intelligence Research, pp.25-187, 2006.

A. I. Coles, M. Fox, D. Long, and A. J. Smith, Planning with problems requiring temporal coordination, Proc. 23rd AAAI Conf. on Artificial Intelligence, 2008.

G. D. Penna, B. Intrigila, D. Magazzeni, and F. Mercorio, Upmurphi: a tool for universal planning on pddl+ problems, Proc. 19th Int. Conf. on Automated Planning and Scheduling (ICAPS), pp.19-23, 2009.

P. Eyerich, R. Mattmüller, and G. Röger, Using the Context-Enhanced Additive Heuristic for Temporal and Numeric Planning, Proc. 19th Int. Conf. on Automated Planning and Scheduling (ICAPS, 2009.
DOI : 10.1007/978-3-642-25116-0_6

J. Löhr, P. Eyerich, T. Keller, and B. Nebel, A planning based framework for controlling hybrid systems, Proc. Int. Conf. on Automated Planning and Scheduling (ICAPS), 2012.

D. F. Ferber, On modeling the tactical planning of oil pipeline networks, Proc. 18th Int. Conf. on Automated Planning and Scheduling (ICAPS, 2012.

E. Burns, J. Benton, W. Ruml, S. Yoon, and M. Do, Anticipatory on-line planning, International Conference on Automated Planning and Scheduling, 2012.

M. Gopal, Control systems: principles and design, 2008.

D. Nau, ¡. , M. Traverso, and P. , Automated Planning: Theory & Practice, 2004.

M. Fox and D. Long, PDDL2.1: An extension of PDDL for expressing temporal planning domains, Journal of Artificial Intelligence Research, pp.20-61, 2003.

S. K. Gupta, D. S. Nau, and W. C. Regli, IMACS: a case study in real-world planning, IEEE Intelligent Systems, vol.13, issue.3, pp.49-60, 1998.
DOI : 10.1109/5254.683210

A. Garrido, E. Onaindia, and F. Barber, A temporal planning system for timeoptimal planning, Progress in AI, 2001.

A. Gerevini, P. Haslum, D. Long, A. Saetti, and Y. Dimopoulos, Deterministic planning in the fifth international planning competition: PDDL3 and experimental evaluation of the planners, Artificial Intelligence, vol.173, issue.5-6, pp.5-6, 2009.
DOI : 10.1016/j.artint.2008.10.012

J. Hoffmann and B. Nebel, The FF planning system: Fast plan generation through heuristic search, Journal of Artificial Intelligence Research, pp.14-253, 2001.

D. Mcdermott, PDDL?the planning domain definition language, 1998.

H. L. Younes, M. L. Littman, D. Weissman, and J. Asmuth, The First Probabilistic Track of the International Planning Competition, Journal of Artitificial Intelligence Research, pp.24-851, 2005.

S. Sanner, Relational dynamic influence diagram language (RDDL): Language description, p.pdf, 2010.

A. Ganek and T. Corbi, The dawning of the autonomic computing era, 00188670 Copyright International Business Machines Corporation, pp.5-5, 2003.
DOI : 10.1147/sj.421.0005

S. Lightstone, Seven software engineering principles for autonomic computing development, Innovations in Systems and Software Engineering, vol.3, issue.1, pp.71-74, 2007.
DOI : 10.1007/s11334-006-0012-x

M. Fox, D. Long, and D. Magazzeni, Plan-based policy-learning for autonomous feature tracking, Proc. of Int. Conf. on Automated Planning and Scheduling (ICAPS, 2012.