Abstract
The paper discusses a distributed approach to multi-agent plan execution and control, where a team of agents may perform actions concurrently in a partially observable environment. Each agent is able to supervise the execution of the actions it is responsible for by means of an on-line monitoring step and to perform agent diagnosis when a failure in the execution of an action has been detected.
The emphasis of the paper is on the mechanism for synthesizing a recovery plan in presence of an action failure. One contribution of the paper concerns an in depth analysis of the characteristics the recovery plan has to satisfy. The most stringent requirement regards that the recovery plan has to be conformant, as the partial observability of the system allows just to estimate the status of the agent and the action effects may be non deterministic.
The paper proposes an approach for synthesizing such a conformant recovery plan based on the adoption of symbolic methods. In particular, the recovery planning is implemented in terms of operations on Ordered Binary Decision Diagrams used for encoding both the belief states and the action models.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
L. Birnbaum, G. Collins, M. Freed, and B. Krulwich, ’Model-based diagnosis of planning failures’, in Proc. AAAI90, pp. 318-323, (1990).
C. Boutilier and R. I. Brafman, ’Partial-order planning with concurrent interacting actions’, Journal of Artificial Intelligence Research, 14, pp. 105-136 (2001).
A. Cimatti and M. Roveri, ’Conformant Planning via Symbolic Model Checking’, Journal of Artificial Intelligence Research 13, pp. 305-338 (2000).
M. Jensen and M. M. Veloso, ’OBDD-based Universal Planning for Synchronized Agents in Non-Deterministic Domains’, Journal of Artificial Intelligence Research 13, pp. 189-226 (2000).
M. Kalech and G.A.Kaminka, ’Towards Model-Based Diagnosis of Coordination Failures’, in Proc. AAAI05, pp. 102-107 (2005).
R. Micalizio and P. Torasso, ’Recovery from Plan Failure in Partially Observable Environments: the long report’, Technical Report www.di.unito.it\ ~micalizi.
R. Micalizio and P. Torasso, ’Diagnosis of Multi-Agent Plans under Partial Observability’, in Proc. 18th International Workshop on Principles of Diagnosis (DX07), pp. 346-353 (2007).
R. Micalizio, P. Torasso and G. Torta, ’Intelligent Supervision of Plan Execution in Multi-Agent Systems’ in International Transactions on Systems Science and Applications, 1(3), pp. 259-267 (2006).
R. Micalizio, and P. Torasso, ’On-LineMonitoring and Diagnosis of Multi-Agent Systems: a Model Based Approach’, Knowledge-Based Systems (special issue on AI 2006), 20(2), pp. 134-142 (2007).
M. D. R-Moreno, G. Brat, N. Muscettola and D. Rijsman, ’Validation of a Multi-Agent Architecture for Planning and Execution’ in Proc. 18th InternationalWorkshop on Principles of Diagnosis (DX07), pp. 368-374 (2007).
Y. Pencole and M.O. Cordier, ’A formal framework for the decentralised diagnosis of large scale discrete event systems and its application to telecommunication networks’, Artificial Intelligence, 164, 121-170, (2005).
N. Carver and V. Lesser, ’Domain monotonicity and the performance of local solutions strategies for cdps-based distributed sensor interpretation and distributed diagnosis’, AAMAS Journal, 6, 35-76, (2003).
C. Wittenven, N. Roos, R. van der Krogt, and M. deWeerdt, ’Diagnosis of single and multi-agent plans’, in Proc. AAMAS05, pp. 805-812 (2005).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag London Limited
About this paper
Cite this paper
Torasso, R.M.P. (2008). Recovery from Plan Failures in Partially Observable Environments. In: Bramer, M., Coenen, F., Petridis, M. (eds) Research and Development in Intelligent Systems XXIV. SGAI 2007. Springer, London. https://doi.org/10.1007/978-1-84800-094-0_24
Download citation
DOI: https://doi.org/10.1007/978-1-84800-094-0_24
Publisher Name: Springer, London
Print ISBN: 978-1-84800-093-3
Online ISBN: 978-1-84800-094-0
eBook Packages: Computer ScienceComputer Science (R0)