A Logic Based Framework for Planning for Mobile Agents
The objective of the paper is twofold. First, to develop a
formal framework for planning for mobile agents. A logical language
based on a temporal logic is proposed that can express a type of
tasks which often arise in network management. Second, to design a
planning algorithm for such tasks. The aim of this paper is to study
the importance of finding plans for mobile agents. Although there
has been a lot of research in mobile agents, not much work has been
done to incorporate planning ideas for such agents. This paper makes
an attempt in this direction. A theoretical study of finding plans for
mobile agents is undertaken. A planning algorithm (based on the
paradigm of mobile computing) is proposed and its space, time, and
communication complexity is analyzed. The algorithm is illustrated
by working out an example in detail.
[1] F. Bacchus and F. Kabanza. Planning for temporally extended goals.
Annals of Mathematics and Artifi cial Intelligence, 22:5-27, 1998.
[2] C. Baral, V. Kreinovich, and R. Trejo. Computational complexity of
planning with temporal goals. In Proceedings of IJCAI, pages 509-514,
2001.
[3] M. Beetz and D. McDermott. Improving robot plans during their
execution. In Proceedings of AIPS, 1994.
[4] P. Bellavista, A. Corradi, C. Federici, R. Montanari, and D. Tibaldi.
Security for mobile agents: issues and challenges. Handbook of mobile
computing: I. Mahgoub and M. Ilyass (eds), 2004.
[5] A. Bieszczad, B. Pagurek, and T. White. Mobile agents for network
management. IEEE Communications Surveys, 1998.
[6] A. Blum and L. Furst. Fast planning through planning graph analysis.
Artifi cial Intelligence, 90:281-300, 1997.
[7] L. Cardelli. Wide area computation. In Proceedings of ICALP, LNCS
1644, pages 10-24, 1999.
[8] E.M. Clarke, E.A. Emerson, and A.P. Sistla. Automatic verifi cation of
fi nite-state concurrent systems using temporal logic specifi cations. ACM
Transactions of Programming Languages and Systems, 8(2):244-263,
1986.
[9] J.E. Cook. Software engineering concerns for mobile agent systems.
In Proceedings of the Workshop on Software Engineering and Mobility,
2001.
[10] A. Fuggetta, G. Picco, and G. Vigna. Understanding code mobility.
IEEE Transactions on Software Engineering, 24(5):342-361, 1998.
[11] M. Ghallab, D. Nau, and P. Traverso. Automated Planning: Theory and
Practice. Morgan Kaufmann Publishers, 2004.
[12] F. Giunchiglia and P. Traverso. Planning as model checking. In
Proceedings of European Conference on Planning, pages 1-20, 1999.
[13] J. Hoffmann and B. Nebel. The ff planning system: Fast plan generation
through heuristic search. Artifi cial Intelligence, 14:253-302, 2001.
[14] D. Kotz and R. Gray. Mobile agents and the future of the internet. ACM
Operating Systems Review, 33(2):7-13, 1999.
[15] H. Levesque. What is planning in the presence of sensing? In
Proceedings of AAAI, 1996.
[16] K. Moizumi. Mobile agents planning problem. In PhD thesis, Dartmouth
College, 1998.
[17] A. Murphy and G. Picco. Reliable communication for highly mobile
agents. Journal of Autonomous Agents and Multi-Agent Systems,
5(1):81-100, 2002.
[18] C.H. Papadimitriou and M. Yannakakis. Shortest paths without a map.
Theoretical Computer Science, 84:127-150, 1991.
[19] M. Pistore and P. Traverso. Planning as model checking for extended
goals in non-deterministic domains. In Proceedings of IJCAI, pages
479-486, 2001.
[20] P. Rodriguez, C. Spanner, and E.W. Biersack. Analysis of web caching
architectures: hierarchical and distributed caching. IEEE Transactions
on networking, 9(4):404-418, 2001.
[21] J.A. Sauter, R. Matthews, H. van dyke Parunak, and S. Brueckner. Evolving
adaptive pheromone path planning mechanisms. In Proceedings of
AAMAS, 2002.
[22] M. Sharma, S. Iyengar, and N. Mandyam. An effi cient distributed
depth fi rst search algorithm. Information Processing Letters, 32:183-
186, 1989.
[23] L. Spalazzi and P. Traverso. A dynamic logic for acting, sensing, and
planning. Logic Computation, 10(6):727-821, 2000.
[24] S. Thiebaux and M. Cordier. Supply restoration in power distribution
systems-a benchmark for planning under uncertainty. In Proceedings of
ECP, 2001.
[25] P. Wojciechowski. Algorithms for location-independent communication
between mobile agents. In Proceedings of AISB -01 Symposium on
Software Mobility and Adaptive Behaviour, 2001.
[1] F. Bacchus and F. Kabanza. Planning for temporally extended goals.
Annals of Mathematics and Artifi cial Intelligence, 22:5-27, 1998.
[2] C. Baral, V. Kreinovich, and R. Trejo. Computational complexity of
planning with temporal goals. In Proceedings of IJCAI, pages 509-514,
2001.
[3] M. Beetz and D. McDermott. Improving robot plans during their
execution. In Proceedings of AIPS, 1994.
[4] P. Bellavista, A. Corradi, C. Federici, R. Montanari, and D. Tibaldi.
Security for mobile agents: issues and challenges. Handbook of mobile
computing: I. Mahgoub and M. Ilyass (eds), 2004.
[5] A. Bieszczad, B. Pagurek, and T. White. Mobile agents for network
management. IEEE Communications Surveys, 1998.
[6] A. Blum and L. Furst. Fast planning through planning graph analysis.
Artifi cial Intelligence, 90:281-300, 1997.
[7] L. Cardelli. Wide area computation. In Proceedings of ICALP, LNCS
1644, pages 10-24, 1999.
[8] E.M. Clarke, E.A. Emerson, and A.P. Sistla. Automatic verifi cation of
fi nite-state concurrent systems using temporal logic specifi cations. ACM
Transactions of Programming Languages and Systems, 8(2):244-263,
1986.
[9] J.E. Cook. Software engineering concerns for mobile agent systems.
In Proceedings of the Workshop on Software Engineering and Mobility,
2001.
[10] A. Fuggetta, G. Picco, and G. Vigna. Understanding code mobility.
IEEE Transactions on Software Engineering, 24(5):342-361, 1998.
[11] M. Ghallab, D. Nau, and P. Traverso. Automated Planning: Theory and
Practice. Morgan Kaufmann Publishers, 2004.
[12] F. Giunchiglia and P. Traverso. Planning as model checking. In
Proceedings of European Conference on Planning, pages 1-20, 1999.
[13] J. Hoffmann and B. Nebel. The ff planning system: Fast plan generation
through heuristic search. Artifi cial Intelligence, 14:253-302, 2001.
[14] D. Kotz and R. Gray. Mobile agents and the future of the internet. ACM
Operating Systems Review, 33(2):7-13, 1999.
[15] H. Levesque. What is planning in the presence of sensing? In
Proceedings of AAAI, 1996.
[16] K. Moizumi. Mobile agents planning problem. In PhD thesis, Dartmouth
College, 1998.
[17] A. Murphy and G. Picco. Reliable communication for highly mobile
agents. Journal of Autonomous Agents and Multi-Agent Systems,
5(1):81-100, 2002.
[18] C.H. Papadimitriou and M. Yannakakis. Shortest paths without a map.
Theoretical Computer Science, 84:127-150, 1991.
[19] M. Pistore and P. Traverso. Planning as model checking for extended
goals in non-deterministic domains. In Proceedings of IJCAI, pages
479-486, 2001.
[20] P. Rodriguez, C. Spanner, and E.W. Biersack. Analysis of web caching
architectures: hierarchical and distributed caching. IEEE Transactions
on networking, 9(4):404-418, 2001.
[21] J.A. Sauter, R. Matthews, H. van dyke Parunak, and S. Brueckner. Evolving
adaptive pheromone path planning mechanisms. In Proceedings of
AAMAS, 2002.
[22] M. Sharma, S. Iyengar, and N. Mandyam. An effi cient distributed
depth fi rst search algorithm. Information Processing Letters, 32:183-
186, 1989.
[23] L. Spalazzi and P. Traverso. A dynamic logic for acting, sensing, and
planning. Logic Computation, 10(6):727-821, 2000.
[24] S. Thiebaux and M. Cordier. Supply restoration in power distribution
systems-a benchmark for planning under uncertainty. In Proceedings of
ECP, 2001.
[25] P. Wojciechowski. Algorithms for location-independent communication
between mobile agents. In Proceedings of AISB -01 Symposium on
Software Mobility and Adaptive Behaviour, 2001.
@article{"International Journal of Information, Control and Computer Sciences:55266", author = "Rajdeep Niyogi", title = "A Logic Based Framework for Planning for Mobile Agents", abstract = "The objective of the paper is twofold. First, to develop a
formal framework for planning for mobile agents. A logical language
based on a temporal logic is proposed that can express a type of
tasks which often arise in network management. Second, to design a
planning algorithm for such tasks. The aim of this paper is to study
the importance of finding plans for mobile agents. Although there
has been a lot of research in mobile agents, not much work has been
done to incorporate planning ideas for such agents. This paper makes
an attempt in this direction. A theoretical study of finding plans for
mobile agents is undertaken. A planning algorithm (based on the
paradigm of mobile computing) is proposed and its space, time, and
communication complexity is analyzed. The algorithm is illustrated
by working out an example in detail.", keywords = "Acting, computer network, mobile agent, mobile computing,planning, temporal logic.", volume = "2", number = "2", pages = "421-9", }
