5 research outputs found
Diverse Trajectory Planning for UAV Control Displays (Demonstration)
ABSTRACT Current UAV control systems can plan optimal trajectories with respect to predefined constraints (waypoints, nofly zones). However when the operator is not satisfied with planned trajectories it is usually very complicated to force the system to change the trajectories in desired way. In this demonstration we solve this problem by innovative UAV control display based on diverse planning algorithm
Diverse Planning for UAV Control and Remote Sensing
Unmanned aerial vehicles (UAVs) are suited to various remote sensing missions, such as measuring air quality. The conventional method of UAV control is by human operators. Such an approach is limited by the ability of cooperation among the operators controlling larger fleets of UAVs in a shared area. The remedy for this is to increase autonomy of the UAVs in planning their trajectories by considering other UAVs and their plans. To provide such improvement in autonomy, we need better algorithms for generating alternative trajectory variants that the UAV coordination algorithms can utilize. In this article, we define a novel family of multi-UAV sensing problems, solving task allocation of huge number of tasks (tens of thousands) to a group of configurable UAVs with non-zero weight of equipped sensors (comprising the air quality measurement as well) together with two base-line solvers. To solve the problem efficiently, we use an algorithm for diverse trajectory generation and integrate it with a solver for the multi-UAV coordination problem. Finally, we experimentally evaluate the multi-UAV sensing problem solver. The evaluation is done on synthetic and real-world-inspired benchmarks in a multi-UAV simulator. Results show that diverse planning is a valuable method for remote sensing applications containing multiple UAVs
The Limits of Strong Privacy Preserving Multi-Agent Planning
Multi-agent planning using MA-STRIPS-related models is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but it is one of the main reasons, why multi-agent planning (MAP) problems cannot be solved centrally. In this paper, we analyze privacy-preserving multi-agent planning (PP-MAP) from the perspective of secure multiparty computation (MPC). We discuss the concept of strong privacy and its implications and present two variants of a novel planner, provably strong privacy-preserving in general. As the main contribution, we formulate the limits of strong privacy-preserving planning in the terms of privacy, completeness and efficiency and show that, for a wide class of planning algorithms, all three properties are not achievable at once. Moreover, we provide a restricted variant of strong privacy based on equivalence classes of planning problems and show that an efficient, complete and strong privacy-preserving planner exists for such restriction
Cooperative Multi-Agent Planning: A survey
[EN] Cooperative multi-agent planning (MAP) is a relatively recent research field that combines technologies,
algorithms, and techniques developed by the Artificial Intelligence Planning and Multi-Agent Systems communities.
While planning has been generally treated as a single-agent task, MAP generalizes this concept by
considering multiple intelligent agents that work cooperatively to develop a course of action that satisfies the
goals of the group.
This article reviews the most relevant approaches to MAP, putting the focus on the solvers that took part
in the 2015 Competition of Distributed and Multi-Agent Planning, and classifies them according to their key
features and relative performance.This work is supported by the GLASS project Grant No. TIN2014-55637-C2-2-R MINECO of the Spanish Ministerio de Economia, Industria y Competitividad, the Prometeo project II/2013/019 funded by the Valencian Government, and the four-year FPI-UPV research scholarship granted to the first author by the Universitat Politecnica de Valencia. Additionally, this research was partially supported by the Czech Science Foundation under Grant No. 15-20433Y CSF.Torreño Lerma, A.; Onaindia De La Rivaherrera, E.; Komenda, A.; Tolba, M. (2017). Cooperative Multi-Agent Planning: A survey. ACM Computing Surveys. 50(6):84:1-84:32. https://doi.org/10.1145/3128584S84:184:32506Eyal Amir and Barbara Engelhardt. 2003. Factored planning. In Proceedings of the 18th International Joint Conference on Artificial Intelligence (IJCAI’03), Vol. 3. 929--935.J. Benton, Amanda J. Coles, and Andrew I. Coles. 2012. Temporal planning with preferences and time-dependent continuous costs. In Proceedings of the 22nd International Conference on Automated Planning and Scheduling (ICAPS’12). 2--10.Andrea Bonisoli, Alfonso E. Gerevini, Alessandro Saetti, and Ivan Serina. 2014. A privacy-preserving model for the multi-agent propositional planning problem. In Proceedings of the 21st European Conference on Artificial Intelligence (ECAI’14). 973--974.Daniel Borrajo. 2013. Multi-agent planning by plan reuse. In Proceedings of the 12th International Conference on Autonomous Agents and Multi-agent Systems (AAMAS’13). 1141--1142.Daniel Borrajo and Susana Fernández. 2015. MAPR and CMAP. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 1--3.Craig Boutilier and Ronen I. Brafman. 2001. Partial-order planning with concurrent interacting actions. J. Artific. Intell. Res. 14 (2001), 105--136.Ronen I. Brafman. 2015. A privacy preserving algorithm for multi-agent planning and search. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI’15). 1530--1536.Ronen I. Brafman and Carmel Domshlak. 2006. Factored planning: How, when, and when not. In Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference. 809--814.Ronen I. Brafman and Carmel Domshlak. 2008. From one to many: Planning for loosely coupled multi-agent systems. In Proceedings of the 18th International Conference on Automated Planning and Scheduling (ICAPS’08). 28--35.Isabel Cenamor, Tomás de la Rosa, and Fernando Fernández. 2014. IBACOP and IBACOP2 planner. In Proceedings of the International Planning Competition (IPC’14).Bradley J. Clement and Edmund H. Durfee. 1999. Top-down search for coordinating the hierarchical plans of multiple agents. In Proceedings of the 3rd Annual Conference on Autonomous Agents (AGENTS’99). ACM, New York, NY, 252--259.Daniel D. Corkill. 1979. Hierarchical planning in a distributed environment. In Proceedings of the 6th International Joint Conference on Artificial Intelligence (IJCAI’79). 168--175.Jeffrey S. Cox and Edmund H. Durfee. 2004. Efficient mechanisms for multiagent plan merging. In Proceedings of the 3rd Conference on Autonomous Agents and Multiagent Systems (AAMAS’04). 1342--1343.Jeffrey S. Cox and Edmund H. Durfee. 2009. Efficient and distributable methods for solving the multiagent plan coordination problem. Multiagent Grid Syst. 5, 4 (2009), 373--408.Matthew Crosby, Anders Jonsson, and Michael Rovatsos. 2014. A single-agent approach to multiagent planning. In Proceedings of the 21st European Conference on Artificial Intelligence (ECAI’14). 237--242.Matthew Crosby, Michael Rovatsos, and Ronald P. A. Petrick. 2013. Automated agent decomposition for classical planning. In Proceedings of the 23rd International Conference on Automated Planning and Scheduling (ICAPS’13). 46--54.Mathijs de Weerdt, André Bos, Hans Tonino, and Cees Witteveen. 2003. A resource logic for multi-agent plan merging. Ann. Math. Artific. Intell. 37, 1-2 (2003), 93--130.Mathijs de Weerdt and Bradley J. Clement. 2009. Introduction to planning in multiagent systems. Multiagent Grid Syst. 5, 4 (2009), 345--355.Keith Decker, Salim Khan, Carl Schmidt, Gang Situ, Ravi Makkena, and Dennis Michaud. 2002. BioMAS: A multi-agent system for genomic annotation. Int. J. Coop. Info. Syst. 11, 3 (2002), 265--292.Keith Decker and Victor R. Lesser. 1992. Generalizing the partial global planning algorithm. Int. J. Coop. Info. Syst. 2, 2 (1992), 319--346.Marie desJardins and Michael Wolverton. 1999. Coordinating a distributed planning system. AI Mag. 20, 4 (1999), 45--53.Marie E. desJardins, Edmund H. Durfee, Charles L. Ortiz, and Michael J. Wolverton. 1999. A survey of research in distributed continual planning. AI Mag. 20, 4 (1999), 13--22.Yannis Dimopoulos, Muhammad A. Hashmi, and Pavlos Moraitis. 2012. -SATPLAN: Multi-agent planning as satisfiability. Knowl.-Based Syst. 29 (2012), 54--62.Jürgen Dix, Héctor Muñoz-Avila, Dana S. Nau, and Lingling Zhang. 2003. IMPACTing SHOP: Putting an AI planner into a multi-agent environment. Ann. Math. Artific. Intell. 37, 4 (2003), 381--407.Edmund H. Durfee. 1999. Distributed Problem Solving and Planning, Gerhard Weiss (ed.). MIT Press,118--149.Edmund H. Durfee and Victor Lesser. 1991. Partial global planning: A coordination framework for distributed hypothesis formation. IEEE Trans. Syst. Man Cybernet. Spec. Issue Distrib. Sensor Netw. 21, 5 (1991), 1167--1183.Eithan Ephrati and Jeffrey S. Rosenschein. 1994. Divide and conquer in multi-agent planning. In Proceedings of the 12th National Conference on Artificial Intelligence (AAAI’94). 375--380.Eithan Ephrati and Jeffrey S. Rosenschein. 1997. A heuristic technique for multi-agent planning. Ann. Math. Artific. Intell. 20, 1–4 (1997), 13--67.Eric Fabre, Loïg Jezequel, Patrik Haslum, and Sylvie Thiébaux. 2010. Cost-optimal factored planning: Promises and pitfalls. In Proceedings of the 20th International Conference on Automated Planning and Scheduling (ICAPS’10). 65--72.Boi Faltings, Thomas Léauté, and Adrian Petcu. 2008. Privacy guarantees through distributed constraint satisfaction. In Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT’08), Vol. 2. IEEE, 350--358.Richard Fikes and Nils J. Nilsson. 1971. STRIPS: A new approach to the application of theorem proving to problem solving. Artific. Intell. 2, 3 (1971), 189--208.Daniel Fišer, Michal Štolba, and Antonín Komenda. 2015. MAPlan. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 8--10.Foundation for Intelligent Physical Agents. 2002. FIPA Interaction Protocol Specification. Retrieved from http://www.fipa.org/repository/ips.php3.Maria Fox and Derek Long. 2003. PDDL2.1: An extension to PDDL for expressing temporal planning domains. J. Artific. Intell. Res. 20 (2003), 61--124.Malik Ghallab, Adele Howe, Craig Knoblock, Drew McDermott, Ashwin Ram, Manuela M. Veloso, Daniel Weld, and David Wilkins. 1998. PDDL—The planning domain definition language. AIPS-98 Planning Committee (1998).Malik Ghallab, Dana Nau, and Paolo Traverso. 2004. Automated Planning. Theory and Practice. Morgan Kaufmann.Barbara J. Grosz, Luke Hunsberger, and Sarit Kraus. 1999. Planning and acting together. AI Mag. 20, 4 (1999), 23--34.Malte Helmert. 2004. A planning heuristic based on causal graph analysis. Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS’04), 161--170.Malte Helmert. 2006. The fast downward planning system. J. Artific. Intell. Res. 26, 1 (2006), 191--246.Malte Helmert and Carmel Domshlak. 2009. Landmarks, critical paths and abstractions: What’s the difference anyway? In Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS’09). 162--169.Malte Helmert, Patrik Haslum, and Jörg Hoffmann. 2007. Flexible abstraction heuristics for optimal sequential planning. In Proceedings of the 17th International Conference on Automated Planning and Scheduling (ICAPS’07). 176--183.Jörg Hoffmann and Bernhard Nebel. 2001. The FF planning system: Fast planning generation through heuristic search. J. Artific. Intell. Res. 14 (2001), 253--302.Jörg Hoffmann, Julie Porteous, and Laura Sebastiá. 2004. Ordered landmarks in planning. J. Artific. Intell. Res. 22 (2004), 215--278.Jan Hrncír, Michael Rovatsos, and Michal Jakob. 2015. Ridesharing on timetabled transport services: A multiagent planning approach. J. Intell. Transportat. Syst. 19, 1 (2015), 89--105.Loïg Jezequel and Eric Fabre. 2012. A#: A distributed version of A* for factored planning. In Proceedings of the 51th IEEE Conference on Decision and Control (CDC’12). 7377--7382.Anders Jonsson and Michael Rovatsos. 2011. Scaling up multiagent planning: A best-response approach. In Proceedings of the 21st International Conference on Automated Planning and Scheduling (ICAPS’11). AAAI, 114--121.Jaume Jordán and Eva Onaindia. 2015. Game-theoretic approach for non-cooperative planning. In Proceedings of the 29th Conference on Artificial Intelligence (AAAI’15). 1357--1363.Froduald Kabanza, Lu Shuyun, and Scott Goodwin. 2004. Distributed hierarchical task planning on a network of clusters. In Proceedings of the 16th International Conference on Parallel and Distributed Computing and Systems (PDCS’04). 139--140.Henry A. Kautz. 2006. Deconstructing planning as satisfiability. In Proceedings of the National Conference on Artificial Intelligence, Vol. 21, 1524.Elena Kelareva, Olivier Buffet, Jinbo Huang, and Sylvie Thiébaux. 2007. Factored planning using decomposition trees. In Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI’07). 1942--1947.Antonín Komenda, Michal Stolba, and Daniel L. Kovacs. 2016. The international competition of distributed and multiagent planners (CoDMAP). AI Mag. 37, 3 (2016), 109--115.Daniel L. Kovacs. 2012. A multi-agent extension of PDDL3.1. In Proceedings of the 3rd Workshop on the International Planning Competition (IPC’12). 19--27.Jonas Kvarnström. 2011. Planning for loosely coupled agents using partial order forward-chaining. In Proceedings of the 21st International Conference on Automated Planning and Scheduling (ICAPS’11). AAAI, 138--145.Victor Lesser, Keith Decker, Thomas Wagner, Norman Carver, Alan Garvey, Bryan Horling, Daniel Neiman, Rodion Podorozhny, M. Nagendra Prasad, Anita Raja, Regis Vincent, Ping Xuan, and X. Q. Zhang. 2004. Evolution of the GPGP/TAEMS domain-independent coordination framework. Auton. Agents Multi-Agent Syst. 9, 1–2 (2004), 87--143.Derek Long, Henry Kautz, Bart Selman, Blai Bonet, Hector Geffner, Jana Koehler, Michael Brenner, Joerg Hoffmann, Frank Rittinger, Corin R. Anderson, Daniel S. Weld, David E. Smith, Maria Fox, and Derek Long. 2000. The AIPS-98 planning competition. AI Mag. 21, 2 (2000), 13--33.Nerea Luis and Daniel Borrajo. 2014. Plan merging by reuse for multi-agent planning. In Proceedings of the 2nd ICAPS Workshop on Distributed and Multi-Agent Planning (DMAP’14). 38--44.Nerea Luis and Daniel Borrajo. 2015. PMR: Plan merging by reuse. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 11--13.Shlomi Maliah, Ronen I. Brafman, and Guy Shani. 2017. Increased privacy with reduced communication in multi-agent planning. In Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS’17). 209--217.Shlomi Maliah, Guy Shani, and Roni Stern. 2014. Privacy preserving landmark detection. In Proceedings of the 21st European Conference on Artificial Intelligence (ECAI’14). 597--602.Shlomi Maliah, Guy Shani, and Roni Stern. 2016. Collaborative privacy preserving multi-agent planning. Auton. Agents Multi-Agent Syst. (2016), 1--38.Felipe Meneguzzi and Lavindra de Silva. 2015. Planning in BDI agents: A survey of the integration of planning algorithms and agent reasoning. Knowl. Eng. Rev. 30, 1 (2015), 1--44.Christian Muise, Nir Lipovetzky, and Miquel Ramirez. 2015. MAP-LAPKT: Omnipotent multi-agent planning via compilation to classical planning. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 14--16.Dana S. Nau, Tsz-Chiu Au, Okhtay Ilghami, Ugur Kuter, J. William Murdock, Dan Wu, and Fusun Yaman. 2003. SHOP2: An HTN planning system. J. Artific. Intell. Res. 20 (2003), 379--404.Raz Nissim and Ronen I. Brafman. 2012. Multi-agent A* for parallel and distributed systems. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’12). 1265--1266.Raz Nissim and Ronen I. Brafman. 2013. Cost-optimal planning by self-interested agents. In Proceedings of the 27th Conference on Artificial Intelligence (AAAI’13).Raz Nissim and Ronen I. Brafman. 2014. Distributed heuristic forward search for multi-agent planning. J. Artific. Intell. Res. 51 (2014), 293--332.Raz Nissim, Ronen I. Brafman, and Carmel Domshlak. 2010. A general, fully distributed multi-agent planning algorithm. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS’10). 1323--1330.Sergio Pajares and Eva Onaindia. 2013. Context-aware multi-agent planning in intelligent environments. Info. Sciences 227 (2013), 22--42.Michal Pechoucek, Martin Rehák, Petr Charvát, Tomáš Vlcek, and Michal Kolar. 2007. Agent-based approach to mass-oriented production planning: Case study. IEEE Trans. Syst. Man Cybernet. Part C 37, 3 (2007), 386--395.Damien Pellier. 2010. Distributed planning through graph merging. In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence (ICAART’10). 128--134.Miquel Ramirez, Nir Lipovetzky, and Christian Muise. 2015. Lightweight Automated Planning ToolKiT. Retrieved from http://lapkt.org/.Prashant P. Reddy and Manuela M. Veloso. 2011. Strategy learning for autonomous agents in smart grid markets. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI’11). 1446--1451.Silvia Richter and Matthias Westphal. 2010. The LAMA planner: Guiding cost-based anytime planning with landmarks. J. Artific. Intell. Res. 39, 1 (2010), 127--177.Valentin Robu, Han Noot, Han La Poutré, and Willem-Jan van Schijndel. 2011. A multi-agent platform for auction-based allocation of loads in transportation logistics. Expert Syst. Appl. 38, 4 (2011), 3483--3491.Óscar Sapena, Eva Onaindia, Antonio Garrido, and Marlene Arangú. 2008. A distributed CSP approach for collaborative planning systems. Eng. Appl. Artific. Intell. 21, 5 (2008), 698--709.Emilio Serrano, Jose M. Such, Juan A. Botía, and Ana García-Fornes. 2013. Strategies for avoiding preference profiling in agent-based e-commerce environments. Appl. Intell. (2013), 1--16.Sven Seuken and Shlomo Zilberstein. 2008. Formal models and algorithms for decentralized decision making under uncertainty. Auton. Agents Multi-Agent Syst. 17, 2 (2008), 190--250.Guy Shani, Shlomi Maliah, and Roni Stern. 2016. Stronger privacy preserving projections for multi-agent planning. In Proceedings of the 26th International Conference on Automated Planning and Scheduling (ICAPS’16). 221--229.Claude E. Shannon. 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27, 3 (1948), 379--423.Evren Sirin, Bijan Parsia, Dan Wu, James Hendler, and Dana Nau. 2004. HTN planning for web service composition using SHOP2. J. Web Semant. 1, 4 (2004), 377--396.Sarath Sreedharan, Yu Zhang, and Subbarao Kambhampati. 2015. A first multi-agent planner for required cooperation (MARC). In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 17--20.Michal Štolba, Daniel Fišer, and Antonín Komenda. 2015. Admissible landmark heuristic for multi-agent planning. In Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS’15). 211--219.Michal Štolba and Antonín Komenda. 2014. Relaxation heuristics for multiagent planning. In Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS’14). 298--306.Michal Štolba and Antonín Komenda. 2015. MADLA: Planning with distributed and local search. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 21--24.Michal Štolba, Jan Tožička, and Antonín Komenda. 2016. Quantifying privacy leakage in multi-agent planning. Proceedings of the 4rd ICAPS Workshop on Distributed and Multi-Agent Planning (DMAP’16). 80--88.Jose M. Such, Ana García-Fornes, Agustín Espinosa, and Joan Bellver. 2012. Magentix2: A privacy-enhancing agent platform. Eng. Appl. Artific. Intell. (2012), 96--109.Milind Tambe. 1997. Towards flexible teamwork. J. Artific. Intell. Res. 7 (1997), 83--124.Alejandro Torreño, Eva Onaindia, and Óscar Sapena. 2012. An approach to multi-agent planning with incomplete information. In Proceedings of the 20th European Conference on Artificial Intelligence (ECAI’12), Vol. 242. IOS Press, 762--767.Alejandro Torreño, Eva Onaindia, and Óscar Sapena. 2014. A flexible coupling approach to multi-agent planning under incomplete information. Knowl. Info. Syst. 38, 1 (2014), 141--178.Alejandro Torreño, Eva Onaindia, and Óscar Sapena. 2014. FMAP: Distributed cooperative multi-agent planning. Appl. Intell. 41, 2 (2014), 606--626.Alejandro Torreño, Eva Onaindia, and Óscar Sapena. 2015. Global heuristics for distributed cooperative multi-agent planning. In Proceedings of the 25th International Conference on Automated Planning and Scheduling (ICAPS’15). 225--233.Alejandro Torreño, Óscar Sapena, and Eva Onaindia. 2015. MH-FMAP: Alternating global heuristics in multi-agent planning. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 25--28.Jan Tožička, Jan Jakubuv, and Antonín Komenda. 2015. PSM-based planners description for CoDMAP 2015 competition. In Proceedings of the Competition of Distributed and Multi-Agent Planners (CoDMAP’15). 29--32.Jan Tožička, Jan Jakubuv, Antonín Komenda, and Michal Pěchouček. 2015. Privacy-concerned multiagent planning. Knowl. Info. Syst. 48, 3 (2016), 581–618.Jan Tožička, Michal Štolba, and Antonín Komenda. 2017. The limits of strong privacy preserving multi-agent planning. In Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS’17). 221--229.Roman van der Krogt. 2007. Privacy loss in classical multiagent planning. In Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT’07). 168--174.Roman van der Krogt. 2009. Quantifying privacy in multiagent planning. Multiagent Grid Syst. 5, 4 (2009), 451--469.David E. Wilkins. 1988. Practical Planning: Extending the Classical AI Planning Paradigm. Morgan Kaufmann.David E. Wilkins and Karen L. Myers. 1998. A multiagent planning architecture. In Proceedings of the 4th International Conference on Artificial Intelligence Planning Systems (AIPS’98). 154--162.Michael Wolverton and Marie desJardins. 1998. Controlling communication in distributed planning using irrelevance reasoning. In Proceedings of the 15th National Conference on Artificial Intelligence (AAAI’98). 868--874.Michael Wooldridge. 1997. Agent-based software engineering. IEEE Proc. Softw. Eng. 144, 1 (1997), 26--37.Yu Zhang and Subbarao Kambhampati. 2014. A formal analysis of required cooperation in multi-agent planning. CoRR abs/1404.5643 (2014). http://arxiv.org/abs/1404.5643