article

Maintenance goals of agents in a dynamic environment: Formulation and policy construction

Authors:

Marcus Bjäreland,

Mutsumi NakamuraAuthors Info & Claims

Artificial Intelligence, Volume 172, Issue 12-13

Pages 1429 - 1469

https://doi.org/10.1016/j.artint.2008.03.005

Published: 01 August 2008 Publication History

Abstract

The notion of maintenance often appears in the AI literature in the context of agent behavior and planning. In this paper, we argue that earlier characterizations of the notion of maintenance are not intuitive to characterize the maintenance behavior of certain agents in a dynamic environment. We propose a different characterization of maintenance and distinguish it from earlier notions such as stabilizability. Our notion of maintenance is more sensitive to a good-natured agent which struggles with an ''adversary'' environment, which hinders her by unforeseeable events to reach her goals (not in principle, but in case). It has a parameter k, referring to the length of non-interference (from exogenous events) needed to maintain a goal; we refer to this notion as k-maintainability. We demonstrate the notion on examples, and address the important but non-trivial issue of efficient construction of maintainability control functions. We present an algorithm which in polynomial time constructs a k-maintainable control function, if one exists, or tells that no such control is possible. Our algorithm is based on SAT Solving, and employs a suitable formulation of the existence of k-maintainable control in a fragment of SAT which is tractable. For small k (bounded by a constant), our algorithm is linear time. We then give a logic programming implementation of our algorithm and use it to give a standard procedural algorithm, and analyze the complexity of constructing k-maintainable controls, under different assumptions such as k=1, and states described by variables. On the one hand, our work provides new concepts and algorithms for maintenance in dynamic environment, and on the other hand, a very fruitful application of computational logic tools. We compare our work with earlier works on control synthesis from temporal logic specification and relate our work to Dijkstra's notion of self-stabilization and related notions in distributed computing.

References

[1]

Abadi, M., Lamport, L. and Wolper, P., Realizable and unrealizable specifications of reactive systems. In: LNCS, vol. 372. Springer. pp. 1-17.]]

Digital Library

[2]

Arora, A. and Gouda, M.G., Closure and convergence: A foundation of fault-tolerant computing. IEEE Transactions on Software Engineering. v19 i11. 1015-1027.]]

Digital Library

[3]

Bacchus, F. and Kabanza, F., Planning for temporally extended goals. Annals of Mathematics and Artificial Intelligence. v22. 5-27.]]

Digital Library

[4]

Baral, C., Eiter, T. and Zhao, J., Using SAT and LP to design polynomial-time algorithms for planning in non-deterministic domains. In: Proc. 20th National Conference on Artificial Intelligence (AAAI '05), AAAI Press. pp. 578-583.]]

Digital Library

[5]

Baral, C., Gelfond, M. and Provetti, A., Representing actions: Laws, observations, and hypothesis. Journal of Logic Programming. v31. 201-243.]]

[6]

Baral, C., Kreinovich, V. and Trejo, R., Computational complexity of planning and approximate planning in the presence of incompleteness. Artificial Intelligence. v122 i1-2. 241-267.]]

Digital Library

[7]

Baral, C., Kreinovich, V. and Trejo, R., Computational complexity of planning with temporal goals. In: Nebel, B. (Ed.), Proc. 17th International Joint Conference on Artificial Intelligence (IJCAI-01), Morgan Kaufmann. pp. 509-514.]]

Digital Library

[8]

Baral, C. and Son, T., Relating theories of actions and reactive control. Electronic Transactions on Artificial Intelligence. v2 i3-4. 211-271.]]

[9]

Baral, C. and Zhao, J., Goal specification in presence of non-deterministic actions. In: de Mántaras, R.L., Saitta, L. (Eds.), Proc. 16th European Conference on Artificial Intelligence (ECAI 2004), IOS Press. pp. 273-277.]]

[10]

M. Barbeau, F. Kabanza, R. St-Denis, Synthesizing plan controllers using real-time goals, in: Proc. 14th International Joint Conference on Artificial Intelligence (IJCAI-95), 1995, pp. 791--800]]

Digital Library

[11]

Barrington, D., Immerman, N. and Straubing, H., On uniformity within NC1. Journal of Computer and System Sciences. v41. 274-306.]]

Digital Library

[12]

M. Ben-Ari, Z. Manna, A. Puneli, The temporal logic of branching time, in: Proc. 8th Symposium on Principles of Programming Languages, 1981, pp. 164--176]]

Digital Library

[13]

P. Bertoli, A. Cimatti, M. Pistore, Strong cyclic planning under partial observability, in: ECAI, 2006, pp. 580--584]]

Digital Library

[14]

P. Bertoli, M. Pistore, Planning with extended goals and partial observability, in: S. Zilberstein, J. Koehler, S. Koenig (Eds.), ICAPS, 2004, pp. 270--278]]

[15]

Brooks, R., A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation. v2 i1. 14-23.]]

[16]

Bylander, T., The computational complexity of propositional strips planning. Artificial Intelligence. v69. 165-204.]]

Digital Library

[17]

S. Ceri, J. Widom, Deriving production rules for constraint maintenance, in: P.M.G. Apers, G. Wiederhold (Eds.), Proc. 15th International Conference on Very Large Data Bases (VLDB-90), 1990, pp. 566--577]]

Digital Library

[18]

Cimatti, A., Pistore, M., Roveri, M. and Traverso, P., Weak, strong, and strong cyclic planning via symbolic model checking. Artificial Intelligence. v147 i1--2. 35-84.]]

Digital Library

[19]

Clarke, E. and Emerson, E., Design and synthesis of synchronization skeletons using branching-time temporal logic. In: LNCS, vol. 131. Springer. pp. 52-71.]]

Digital Library

[20]

Clarke, E., Emerson, E. and Sistla, A., Automatic verification of finite-state concurrent systems using temporal logic specifications. ACM Transactions on Programming Languages and Systems. v8 i2. 244-263.]]

Digital Library

[21]

Daniele, M., Traverso, P. and Vardi, M., Strong cyclic planning revisited. In: LNCS/LNAI, vol. 1809. Springer. pp. 35-48.]]

Digital Library

[22]

Dantsin, E., Eiter, T., Gottlob, G. and Voronkov, A., Complexity and expressive power of logic programming. ACM Computing Surveys. v33 i3. 374-425.]]

Digital Library

[23]

G. De Giacomo, R. Reiter, M. Soutchanski, Execution monitoring of high-level robot programs, in: Proc. Sixth Conference on Principles of Knowledge Representation and Reasoning (KR-98), 1998, pp. 453--465]]

[24]

Dijkstra, E.W., Self-stabilizing systems in spite of distributed control. CACM. v17 i11. 644-843.]]

Digital Library

[25]

Dowling, W. and Gallier, J.H., Linear-time algorithms for testing the satisfiability of propositional Horn theories. Journal of Logic Programming. v3. 267-284.]]

[26]

M. Drummond, Situation control rules, in: Proc. First International Conference on Principles of Knowledge Representation and Reasoning (KR-89), 1989, pp. 103--113]]

Digital Library

[27]

Dunne, P., Laurence, M. and Wooldridge, M., Complexity results for agent design problems. Annals of Mathematics, Computing & Teleinformatics. v1 i1. 19-36.]]

[28]

Dunne, P. and Wooldridge, M., Optimistic and disjunctive agent design problems. In: Castelfranchi, C., Lespérance, Y. (Eds.), LNCS, vol. 1986. Springer. pp. 1-14.]]

Digital Library

[29]

Eiter, T., Faber, W., Leone, N. and Pfeifer, G., Declarative problem-solving using the DLV system. In: Minker, J. (Ed.), Logic-Based Artificial Intelligence, Kluwer. pp. 79-103.]]

Digital Library

[30]

Emerson, E., Temporal and modal logics. In: van, J. (Ed.), Handbook of Theoretical Computer Science, vol. B, Elsevier.]]

Digital Library

[31]

Erol, K., Subrahmanian, V. and Nau, D., Complexity, decidability and undecidability results for domain-independent planning. Artificial Intelligence. v76. 75-88.]]

Digital Library

[32]

Fikes, R.E. and Nilsson, N.J., Strips: A new approach to the application of theorem proving to problem solving. Artificial Intelligence. v2 i3--4. 189-208.]]

[33]

Gelfond, M. and Lifschitz, V., Classical negation in logic programs and disjunctive databases. New Generation Computing. v9. 365-385.]]

[34]

Gelfond, M. and Lifschitz, V., Representing action in extended logic programs. In: Proc. Joint International Conference and Symposium on Logic Programming (JICSLP'92), MIT Press. pp. 559-573.]]

[35]

Ghallab, M., Nau, D. and Traverso, P., Automated Planning---Theory and Practice. 2004. Morgan Kaufmann.]]

Digital Library

[36]

Ginsberg, M.L., Universal planning: An (almost) universally bad idea. AI Magazine. v10 i4. 40-44.]]

Digital Library

[37]

Harding, A., Ryan, M. and Schobbens, P.-Y., A new algorithm for strategy synthesis in ltl games. In: Halbwachs, N., Zuck, L.D. (Eds.), LNCS, vol. 3440. Springer. pp. 477-492.]]

Digital Library

[38]

Immerman, N., Descriptive Complexity. 1999. Springer.]]

[39]

R.M. Jensen, M.M. Veloso, M.H. Bowling, OBDD-based optimistic and strong cyclic adversarial planning, in: Proc. 6th European Conference on Planning (ECP-01), 2001]]

[40]

R.M. Jensen, M.M. Veloso, R.E. Bryant, Fault tolerant planning: Toward probabilistic uncertainty models in symbolic non-deterministic planning, in: S. Zilberstein, J. Koehler, S. Koenig (Eds.), Proc. 14th International Conference on Automated Planning and Scheduling (ICAPS 2004), 2004, pp. 335--344]]

[41]

Kabanza, F., Barbeau, M. and St-Denis, R., Planning control rules for reactive agents. Artificial Intelligence. v95 i1. 67-113.]]

Digital Library

[42]

L.P. Kaelbling, S.J. Rosenschein, Action and planning in embedded agents, in: Maes {47}, pp. 35--48]]

Digital Library

[43]

Kuratowski, C., Topology I. 1966. Academic Press, New York.]]

[44]

U.D. Lago, M. Pistore, P. Traverso, Planning with a language for extended goals, in: AAAI/IAAI, 2002, pp. 447--454]]

Digital Library

[45]

Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S. and Scarcello, F., The DLV system for knowledge representation and reasoning. ACM Transactions on Computational Logic. v7 i3. 499-562.]]

Digital Library

[46]

M.L. Littman, Probabilistic propositional planning: Representations and complexity, in: Proc. 14th National Conference on Artificial Intelligence and 9th Innovative Applications of Artificial Intelligence Conference (AAAI/IAAI 1997), 1997, pp. 748--754]]

Digital Library

[47]

In: Maes, P. (Ed.), Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back, MIT Press.]]

Digital Library

[48]

Manna, Z. and Pnueli, A., The Temporal Logic of Reactive and Concurrent Systems Specification. 1992. Springer.]]

Digital Library

[49]

Manna, Z. and Wolper, P., Synthesis of communicating processes from temporal logic specifications. ACM Transactions on Programming Languages and Systems. v6 i1. 68-93.]]

Digital Library

[50]

Minoux, M., LTUR: A simplified linear time unit resolution for Horn formulae and computer implementation. Information Processing Letters. v29. 1-12.]]

Digital Library

[51]

Invariance, maintenance and other declarative objectives of triggers---a formal characterization of active databases. In: Lloyd, J. (Ed.), LNAI, vol. 1861. Springer. pp. 1210-1224.]]

Digital Library

[52]

Nakamura, M., Baral, C. and Bjæreland, M., Maintainability: A weaker stabilizability like notion for high level control. In: Proc. 17th National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence (AAAI/IAAI 2000), AAAI Press. pp. 62-67.]]

Digital Library

[53]

Niemelä, I., Simons, P. and Syrjänen, T., Smodels: A system for answer set programming. In: Baral, C., Truszczyński, M. (Eds.), Proc. 8th International Workshop on Non-Monotonic Reasoning (NMR'2000),]]

[54]

Niyogi, R. and Sarkar, S., Logical specification of goals. In: Ghosh, R.K., Misra, D. (Eds.), Proc. 3rd International Conference on Information Technology (CIT 2001), Tata McGraw-Hill. pp. 77-82.]]

[55]

Ortiz, C., A commonsense language for reasoning about causation and rational action. Artificial Intelligence. v111 i2. 73-130.]]

Digital Library

[56]

Ozveren, O., Willsky, A. and Antsaklis, P., Stability and stabilizability of discrete event dynamic systems. Journal of ACM. v38 i3. 730-752.]]

Digital Library

[57]

Papadimitriou, C.H., Computational Complexity. 1994. Addison-Wesley.]]

[58]

Passino, K. and Burgess, K., Stability Analysis of Discrete Event Systems. 1998. John Wiley and Sons.]]

[59]

N. Piterman, A. Pnueli, Y. Sa'ar, Synthesis of reactive(1) designs, in: VMCAI, 2006, pp. 364--380]]

Digital Library

[60]

A. Pnueli, R. Rosner, On the synthesis of a reactive module, in: Proc. 16th Annual ACM Symposium on Principles of Programming Languages (POPL 1989), 1989, pp. 179--190]]

Digital Library

[61]

Ramadge, P. and Wonham, W., Modular feedback logic for discrete event systems. SIAM Journal of Control and Optimization. v25 i5. 1202-1217.]]

Digital Library

[62]

Ramadge, P. and Wonham, W., Supervisory control of a class of discrete event process. SIAM Journal of Control and Optimization. v25 i1. 206-230.]]

Digital Library

[63]

Reiter, R., Knowledge in Action: Logical Foundation for Describing and Implementing Dynamical Systems. 2001. MIT Press.]]

Digital Library

[64]

J. Rintanen, Complexity of planning with partial observability, in: S. Zilberstein, J. Koehler, S. Koenig, (Eds.), Proc. 14th International Conference on Automated Planning and Scheduling (ICAPS 2004), 2004, pp. 345--354]]

[65]

Simons, P., Niemelä, I. and Soininen, T., Extending and implementing the stable model semantics. Artificial Intelligence. v138. 181-234.]]

Digital Library

[66]

Sontag, E., Stability and stabilization: Discontinuities and the effect of disturbances. In: Clarke, F., Stern, R. (Eds.), Proc. NATO Advanced Study Institute, Kluwer. pp. 551-598.]]

[67]

Weld, D. and Etzioni, O., The first law of robotics (a call to arms). In: Proc. Twelfth National Conference on Artificial Intelligence (AAAI-94), AAAI Press. pp. 1042-1047.]]

Digital Library

[68]

In: Widom, J., Ceri, S. (Eds.), Active Database Systems: Triggers and Rules For Advanced Database Processing, Morgan Kaufmann.]]

Digital Library

[69]

Wooldridge, M., The computational complexity of agent design problems. In: Proc. Fourth International Conference on Multi-Agent Systems (ICMAS 2000), IEEE Press. pp. 341-348.]]

Digital Library

Cited By

Duff SThangarajah JHarland J(2014)MAINTENANCE GOALS IN INTELLIGENT AGENTSComputational Intelligence10.1111/coin.1200030:1(71-114)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1111/coin.12000
Schwind NOkimoto TInoue KChan HRibeiro TMinami KMaruyama HGini MShehory OIto TJonker C(2013)Systems resilienceProceedings of the 2013 international conference on Autonomous agents and multi-agent systems10.5555/2484920.2485043(785-788)Online publication date: 6-May-2013
https://dl.acm.org/doi/10.5555/2484920.2485043
Hindriks Kvan der Hoek Wvan Riemsdijk MSierra CCastelfranchi CDecker KSichman J(2009)Agent programming with temporally extended goalsProceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 110.5555/1558013.1558031(137-144)Online publication date: 10-May-2009
https://dl.acm.org/doi/10.5555/1558013.1558031

Index Terms

Maintenance goals of agents in a dynamic environment: Formulation and policy construction
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Intelligent agents
    2. Knowledge representation and reasoning
      1. Logic programming and answer set programming
2. Theory of computation
  1. Logic
    1. Constraint and logic programming

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cover image Artificial Intelligence

Artificial Intelligence Volume 172, Issue 12-13

August, 2008

185 pages

ISSN:0004-3702

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Copyright © Elsevier B.V. © 2008.

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Elsevier Science Publishers Ltd.

United Kingdom

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Published: 01 August 2008

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Cited By

Duff SThangarajah JHarland J(2014)MAINTENANCE GOALS IN INTELLIGENT AGENTSComputational Intelligence10.1111/coin.1200030:1(71-114)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1111/coin.12000
Schwind NOkimoto TInoue KChan HRibeiro TMinami KMaruyama HGini MShehory OIto TJonker C(2013)Systems resilienceProceedings of the 2013 international conference on Autonomous agents and multi-agent systems10.5555/2484920.2485043(785-788)Online publication date: 6-May-2013
https://dl.acm.org/doi/10.5555/2484920.2485043
Hindriks Kvan der Hoek Wvan Riemsdijk MSierra CCastelfranchi CDecker KSichman J(2009)Agent programming with temporally extended goalsProceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 110.5555/1558013.1558031(137-144)Online publication date: 10-May-2009
https://dl.acm.org/doi/10.5555/1558013.1558031

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