Organizing the aggregate: Languages for spatial computing

Formal and Practical Aspects of Domain-Specific Languages: Recent Developments

Volumn , Issue , 2013, Pages 436-501

  Beal, Jacob ^a   Dulman, Stefan ^b   Viroli, Mirko ^c   Correll, N ^d   Usbeck, Kyle ^a  

^a BBN TECHNOLOGIES   (United States)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^c UNIVERSITY OF BOLOGNA   (Italy)

^d UCB 450   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84931098762     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-4666-2092-6.ch016     Document Type: Chapter

References (210)

1. Abdelzaher, T., Blum, B., Cao, Q., Chen, Y., Evans, D., & George, J. ... Krishnamurthy, S. (2004). Envirotrack: Towards an environmental computing paradigm for distributed sensor networks. In Proceedings of the 24th International Conference on Distributed Computing Systems (pp. 582-589). IEEE.
2. Abelson, H., Allen, D., Coore, D., Hanson, C., Homsy, G., & Knight, T. Jr (2000). Amorphous computing. Communications of the ACM, 43(5), 74-82. doi:10.1145/332833.332842
3. Allen, E., Chase, D., Hallett, J., Luchangco, V., Maessen, J.-W., Ryu, S., Jr., G. L. S., ... Tobin-Hochstadt, S. (2008). The Fortress language specification version 1.0. Sun Microsystems.
4. Alur, R., & Henzinger, T. (1999). Reactive modules. Formal Methods in System Design, 15(1), 7-48. doi:10.1023/A:1008739929481
5. Alvaro, P. (2009). Dedalus: Datalog in time and space. Technical report. DTIC Document.
6. Annaratone, M., Arnould, E., Gross, T., Kung, H. T., Lam, M., Menzilcioglu, O., & Webb, J. A. (1987). The warp computer: Architecture, implementation, and performance. IEEE Transactions on Computers C, 36(12), 1523-1538. doi:10.1109/TC.1987.5009502
7. Armstrong, J. (2007). A history of Erlang. InHOPL III Proceedings of the Third ACM SIGPLAN Conference on History of Programming Languages (pp. 6-1 - 6-26).
8. ASCAPE. (2011). Ascape guide. Retrieved from http://ascape.sourceforge.net/
9. Ashley-Rollman, M., Goldstein, S., Lee, P., Mowry, T., & Pillai, P. (2007). Meld: A declarative approach to programming ensembles. InProceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2794-2800).
10. Ashley-Rollman, M. P., Lee, P., Goldstein, S. C., Pillai, P., & Campbell, J. D. (2009). Language for large ensembles of independently executing nodes. InProceedings of the International Conference on Logic Programming (ICLP '09) (pp. 265-280).
11. Bachrach, J. (2009). Programming chained robotics in the gas programming language. Technical report. Makani Power.
12. Bachrach, J., & Beal, J. (2007). Building spatial computers. Technical Report MIT-CSAIL-TR-2007-017, MIT.
13. Bachrach, J., Beal, J., & McLurkin, J. (2010). Composable continuous space programs for robotic swarms. Neural Computing & Applications, 19(6), 825-847. doi:10.1007/s00521-010-0382-8
14. Barney, B. (Retrieved Feb. 20, 2012). Introduction to parallel computing. Retrieved from https://computing.llnl.gov/tutorials/parallel_comp/
15. Bauer, B., Müller, J., & Odell, J. (2001). Agent UML: A formalism for specifying multiagent interaction. In Agent-Oriented Software Engineering, Volume 1957, (pp. 91-103).
16. Technologies, B. B. N. (2011). Cougaar: The cognitive agent architecture. Retrieved from http://cougaar.org
17. Beal, J. (2004). Programming an amorphous computational medium. In Unconventional Programming Paradigms International Workshop, volume 3566 of Lecture Notes in Computer Science, (pp. 121-136). Springer Berlin.
18. Beal, J. (2009). Dynamically defined processes for spatial computers. InSpatial Computing Workshop (pp. 206-211).
19. Beal, J. (2010). A basis set of operators for space-time computations. InSpatial Computing Workshop (pp. 91-97).
20. Beal, J., & Bachrach, J. (2006). Infrastructure for engineered emergence on sensor/actuator networks. IEEE Intelligent Systems, 21(2), 10-19. doi:10.1109/MIS.2006.29
21. Beal, J., Lu, T., & Weiss, R. (2011). Automatic compilation from high-level languages to genetic regulatory networks. PLoS ONE, 6(8), E22490. doi:10.1371/journal.pone.0022490
22. Beal, J., & Usbeck, K. (2011). On the evaluation of space-time functions. InSelf-Organizing Self-Adaptive Spatial Computing Workshop (pp. 49-54).
23. Berkeley Software 2009 iGem Team (October 2009, Retrieved May 10, 2010.). Eugene. Retrieved from http://2009.igem.org/Team:Berkeley_Software/Eugene.
24. Beydoun, G., Low, G., Henderson-Sellers, B., Mouratidis, H., Gomez-Sanz, J., Pavon, J., & Gonzalez-Perez, C. (2009). FAML: A generic metamodel for MAS development. IEEE Transactions on Software Engineering, 35(6), 841-863. doi:10.1109/TSE.2009.34
25. Blumofe, R. D., Joerg, C. F., Kuszmaul, B. C., Leiserson, C. E., Randall, K. H., & Zhou, Y. (1995). CILK: An efficient multithreaded runtime system. InProceedings of the Fifth ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP) (pp. 207-216).
26. Borcea, C., Intanagonwiwat, C., Kang, P., Kremer, U., & Iftode, L. (2004). Spatial programming using smart messages: Design and implementation. In Proceedings of 24th International Conference on Distributed Computing Systems (pp. 690-699). IEEE.
27. Bordignon, M., Stoy, K., & Schultz, U. P. (2011a). Generalized programming of modular robots through kinematic configurations. In2011 IEEE/ RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3659-3666).
28. Bordignon, M., Stoy, K., & Schultz, U. P. (2011b). Robust and reversible execution of self-reconfiguration sequences. Robotica, 29(1), 35-57. doi:10.1017/S0263574710000664
29. Boulis, A., Han, C., Shea, R., & Srivastava, M. (2007). Sensorware: Programming sensor networks beyond code update and querying. Pervasive and Mobile Computing, 3(4), 386-412. doi:10.1016/j.pmcj.2007.04.007
30. Butera, W. (2002). Programming a paintable computer. PhD thesis, MIT, Cambridge, MA, USA.
31. Butera, W. (2007). Text display and graphics control on a paintable computer. InInternational Conference on Self-Adaptive and Self-Organizing Systems (pp. 45-54).
32. Calidonna, C., & Furnari, M. (2004). The cellular automata network compiler system: Modules and features. In International Conference on Parallel Computing in Electrical Engineering (pp. 271-276).
33. Cardelli, L. (2005). Brane calculi. In V. Danos & V. Schächter (Eds.), International Conference on Computational Methods in Systems Biology (CMSB 2004), Revised Selected Papers, volume 3082 of Lecture Notes in Computer Science, (pp. 257-278). Springer.
34. Cardelli, L., & Gardner, P. (2010). Processes in space. In F. Ferreira, B. Löwe, E. Mayordomo, & L. M. Gomes (Eds.), Programs, Proofs, Processes, 6th Conference on Computability in Europe, CiE 2010, volume 6158 of Lecture Notes in Computer Science, (pp. 78-87). Springer.
35. Cardelli, L., & Gordon, A. D. (2000). Mobile ambients. Theoretical Computer Science, 240(1), 177-213. doi:10.1016/S0304-3975(99)00231-5
36. Caspi, E., Chu, M., Huang, R., Yeh, J., Wawrzynek, J., & DeHon, A. (2000). Stream computations organized for reconfigurable execution (score). InConference on Field Programmable Logic and Applications (FPL), (pp. 605-614).
37. Centre for Policy Modelling. (2011). Strictly declarative modelling language. Retrieved from http://cfpm.org/sdml/
38. Chapel. (2011). Chapel language specification version 0.82. Cray, Inc.
39. Chen, J., Mundy, J., Bai, Y., Chan, S.-M. C., Petrica, P., & Bahar, R. I. (2003). A probabilistic approach to nano-computing. In Workshop on Non-Silicon Computation, (pp. 1-8).
40. Chou, H.-H., Huang, W., & Reggia, J. A. (2002). The trend cellular automata programming environment. Simulation, 78(2), 59-75. doi:10.1177/0037549702078002204
41. Christensen, A., O'Grady, R., & Dorigo, M. (2007). Morphology control in a multirobot system. IEEE Robotics & Automation Magazine, 14(4), 18-25. doi:10.1109/M-RA.2007.908970
42. Christensen, D. J., Schultz, U. P., & Moghadam, M. (2011). The assemble and animate control framework for modular reconfigurable robots. In IROS Workshop on Reconfigurable Modular Robotics (pp. 1-6).
43. Chu, D., Tavakoli, A., Popa, L., & Hellerstein, J. (2006). Entirely declarative sensor network systems. In Proceedings of the 32nd International Conference on Very Large Data Bases, (pp.1203-1206). VLDB Endowment.
44. Ciciriello, P., Mottola, L., & Picco, G. (2006). Building virtual sensors and actuators over logical neighborhoods. In Proceedings of the International Workshop on Middleware for Sensor Networks, (pp. 19-24). ACM.
45. Collier, N., & North, M. (2011). Repast SC++: A platform for large-scale agent-based modeling. Large-Scale Computing Techniques for Complex System Simulations, 80, 81-109.
46. Collins, R. L. (2011). Data-driven programming abstractions and optimization for multi-core platforms. PhD thesis, Columbia University.
47. Coore, D. (1999). Botanical computing: A developmental approach to generating interconnect topologies on an amorphous computer. PhD thesis, MIT.
48. Correll, N., & Martinoli, A. (2011). Modeling self-organized aggregation in a swarm of miniature robots. The International Journal of Robotics Research. Special Issue on Stochasticity in Robotics and Biological Systems, 30(5), 615-626.
49. Costa, P., Mottola, L., Murphy, A., & Picco, G. (2006). Teenylime: Transiently shared tuple space middleware for wireless sensor networks. In Proceedings of the International Workshop on Middleware for Sensor Networks (pp. 43-48). ACM.
50. Couderc, P., & Banatre, M. (2003). Ambient computing applications: an experience with the spread approach. In Hawaii International Conference on System Sciences (HICSS' 03) (pp. 9-17).
51. Czar, M., Cai, Y., & Peccoud, J. (2009). Writing DNA with genocad. Nucleic Acids Research, 37(W), W40-W47.
52. Czech Technical Institute Agent Technology Center. (2011). Aglobe. Retrieved from http://agents.felk.cvut.cz/aglobe/
53. DeHon, A. (2002). Very large scale spatial computing. In Unconventional Models of Computation. In Lecture Notes in Computer Science (Vol. 2509, pp. 27-37). Springer.
54. DeHon, A., & Wawrzynek, J. (1999). Reconfigurable computing: What, why, and implications for design automation. In Design Automation Conference (DAC), (pp. 610-615).
55. deLorimier, M., Kapre, N., Mehta, N., & DeHon, A. (2011). Spatial hardware implementation for sparse graph algorithms in graphstep. ACM Transactions on Autonomous and Adaptive Systems, 6(3), 17:1-17:20.
56. Dewey, D., Ashley-Rollman, M., Rosa, M. D., Goldstein, S., Mowry, T., & Srinivasa, S. ... Campbell, J. (2008). Generalizing metamodules to simplify planning in modular robotic systems. InProceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, (pp. 1338-1345).
57. D'Hondt, E., & D'Hondt, T. (2001a). Amorphous geometry. InEuropean Conference on Artificial Life 2001, (pp. 645-648).
58. D'Hondt, E., & D'Hondt, T. (2001b). Experiments in amorphous geometry. In 2001 International Conference on Artificial Intelligence (pp. 285-290).
59. Dietrich, C. (2011). Pymorphous: Python language extensions for spatial computing. Retrieved from http://pymorphous.googlecode.com
60. Duckham, M., Nittel, S., & Worboys, M. (2005). Monitoring dynamic spatial fields using responsive geosensor networks. In Proceedings of the 13th Annual ACM International Workshop on Geographic Information Systems (GIS '05) (pp. 51-60). New York, NY: ACM.
61. Dunkels, A., Gronvall, B., & Voigt, T. (2004). Contiki-a lightweight and flexible operating system for tiny networked sensors. In 29th Annual IEEE International Conference on Local Computer Networks, (pp. 455-462). IEEE.
62. Eckart, J. D. (1997). Cellang: Language reference manual. Radford University.
63. Engstrom, B. R., & Cappello, P. R. (1989). The SDEF programming system. Journal of Parallel and Distributed Computing, 7(2), 201-231. doi:10.1016/0743-7315(89)90018-X
64. Erlang. (2011). Erlang reference manual user's guide version 5.9. Ericsson AB.
65. Ferscha, A., Hechinger, M., Riener, A., dos Santos Rocha, M., Zeidler, A., Franz, M., & Mayrhofer, R. (2008). Peer-it: Stick-on solutions for networks of things. Pervasive and Mobile Computing, 4(3), 448-479. doi:10.1016/j.pmcj.2008.01.003
66. Finin, T., Fritzson, R., McKay, D., & McEntire, R. (1994). Kqml as an agent communication language. In Proceedings of the Third International Conference on Information and Knowledge Management (CIKM '94) (pp. 456-463). New York, NY: ACM.
67. Fok, C., Roman, G., & Lu, C. (2005). Rapid development and flexible deployment of adaptive wireless sensor network applications. In Proceedings of the 25th IEEE International Conference on Distributed Computing Systems, (pp. 653-662). IEEE.
68. Forrest, S., & Jones, T. (1994). Modeling complex adaptive systems with echo. Complex systems: Mechanisms of adaptation (pp. 3-21).
69. Frank, C., & Romer, K. (2005). Algorithms for generic role assignment in wireless sensor networks. In Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems (pp. 230-242). ACM.
70. Friedman-Hill, E. (2008). JESS, the rule engine for the Java platform. Retrieved from http://herzberg.ca.sandia.gov/jess/
71. Freiwald, U., & Weimar, J. (2002). The java based cellular automata simulation system Jcasim. Future Generation Computer Systems, 18, 995-1004. doi:10.1016/S0167-739X(02)00078-X
72. Gay, D., Levis, P., Von Behren, R., Welsh, M., Brewer, E., & Culler, D. (2003). The NesC language: A holistic approach to networked embedded systems. ACM Sigplan Notices, 38(5), 1-11. doi:10.1145/780822.781133
73. Gayle, O., & Coore, D. (2006). Self-organizing text in an amorphous environment. In International Conference on Complex Systems, (pp. 1-10).
74. Gelernter, D., & Carriero, N. (1992). Coordination languages and their significance. Communications of the ACM, 35(2), 97-107. doi:10.1145/129630.129635
75. George Mason University Evolutionary Computation Laboratory and Center for Social Complexity. (2011). MASON multiagent simulation. Retrieved from http://cs.gmu.edu/~eclab/projects/mason/
76. Giavitto, J.-L., Godin, C., Michel, O., & Zemyslaw Prusinkiewicz, P. (2002). Computational models for integrative and developmental biology. Technical Report 72-2002, Univerite d'Evry, LaMI.
77. Giavitto, J.-L., Michel, O., Cohen, J., & Spicher, A. (2004). Computation in space and space in computation. Technical Report 103-2004, Univerite d'Evry, LaMI.
78. Giavitto, J.-L., & Spicher, A. (2008). Topological rewriting and the geometrization of programming. Physica D. Nonlinear Phenomena, 237(9), 1302-1314. doi:10.1016/j.physd.2008.03.039
79. Gillespie, D. T. (1977). Exact stochastic simulation of coupled chemical reactions. Journal of Physical Chemistry, 81(25), 2340-2361. doi:10.1021/j100540a008
80. Gilpin, K., Kotay, K., Rus, D., & Vasilescu, I. (2008). Miche: Modular shape formation by self-disassembly. The International Journal of Robotics Research, 27, 345-372. doi:10.1177/0278364907085557
81. Govett, M., Middlecoff, J., Hart, L., Henderson, T., & Schaffer, D. (2003). The scalable modeling system: Directive-based code parallelization for distributed and shared memory computers. Parallel Computing, 29(8), 995-1020. doi:10.1016/S0167-8191(03)00084-X
82. Grelck, C., Penczek, F., & Trojahner, K. (2007). Caos: A domain-specific language for the parallel simulation of cellular automata. In Parallel Computing Technologies, 9th International Conference (PaCT'07) (pp. 410-417). Springer-Verlag.
83. Gropp, W., Lusk, E., & Skjellum, A. (1994). Using MPI: Portable parallel programming with the message passing interface. Cambridge, MA: MIT Press.
84. Grumbach, S., & Wang, F. (2010). Netlog, a rule-based language for distributed programming (pp. 88-103). Practical Aspects of Declarative Languages. doi:10.1007/978-3-642-11503-5_9
85. Gulyás, L., Kozsik, T., & Corliss, J. (1999). The multi-agent modelling language and the model design interface. Journal of Artificial Societies and Social Simulation, 2(3), 8.
86. Gulyás, L., Kozsik, T., & Fazekas, S. (2011). Multi-agent modeling language MAML. Retrieved from http://www.maml.hu/
87. Gummadi, R., Gnawali, O., & Govindan, R. (2005). Macro-programming wireless sensor networks using kairos (pp. 466-466). Distributed Computing in Sensor Systems.
88. Hahn, C. (2008). A domain specific modeling language for multiagent systems. In Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems-Volume 1 (pp. 233-240). International Foundation for Autonomous Agents and Multiagent Systems.
89. Hamann, H., Stradner, J., Schmickl, T., & Crailsheim, K. (2010). A hormone-based controller for evolutionary multi-modular robotics: from single modules to gait learning. In IEEE Congress on Evolutionary Computation (CEC'10) (pp. 244-251).
90. Heinzelman, W., Murphy, A., Carvalho, H., & Perillo, M. (2004). Middleware to support sensor network applications. IEEE Network, 18(1), 6-14. doi:10.1109/MNET.2004.1265828
91. Helsinger, A., Thome, M., & Wright, T. (2004). Cougaar: A scalable, distributed multi-agent architecture. In IEEE International Conference on Systems, Man and Cybernetics, Volume 2, (pp. 1910-1917). IEEE.
92. Hnat, T., Sookoor, T., Hooimeijer, P., Weimer, W., & Whitehouse, K. (2008). Macrolab: A vector-based macroprogramming framework for cyber-physical systems. In Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (pp. 225-238). ACM.
93. Holzmann, C., & Ferscha, A. (2010). A framework for utilizing qualitative spatial relations between networked embedded systems. Pervasive and Mobile Computing, 6(3), 362-381. doi:10.1016/j.pmcj.2010.03.001
94. HPF. (1997). High performance Fortran language specification, Version 2.0. High Performance Fortran Forum.
95. Huget, M. (2005). Modeling languages for multiagent systems. Agent-Oriented Software Engineering (AOSE-2005) (pp. 1-12).
96. Huzita, H., & Scimemi, B. (1989). The algebra of paper-folding. In First International Meeting of Origami Science and Technology (pp. 215-222).
97. IEEE. Computer Society. (2011). Foundation for intelligent physical agents. Retrieved from http://www.fipa.org/
98. Igarashi, A., Pierce, B. C., & Wadler, P. (2001). Featherweight Java: A minimal core calculus for Java and GJ. ACM Transactions on Programming Languages and Systems, 23(3), 396-450. doi:10.1145/503502.503505
99. Inchiosa, M., & Parker, M. (2002). Overcoming design and development challenges in agent-based modeling using ASCAPE. Proceedings of the National Academy of Sciences of the United States of America, 99(Suppl 3), 7304-7310. doi:10.1073/ pnas.082081199
100. nd International Conference on Architecture of Computing Systems ARCS 2009, LNCS 5455, (pp. 246-257).
101. Jones, T., & Forrest, S. (2011). An introduction to SFI echo. Retrieved from http://tuvalu.santafe.edu/pth/echo/how-to/how-to.html
102. Jozwiak, L., Nedjah, N., & Figueroa, M. (2010). Modern development methods and tools for embedded reconfigurable systems: A survey. Integration, the VLSI Journal, 43(1), 1-33.
103. Kinny, D. (2002). The ψ calculus: An algebraic agent language. In J.-J. Meyer & M. Tambe (Eds.), Intelligent Agents VIII, volume 2333 of Lecture Notes in Computer Science, (pp. 32-50). Berlin, Germany: Springer.
104. Klavins, E., Ghrist, R., & Lipsky, D. (2006). A grammatical approach to self-organizing robotic systems. IEEE Transactions on Automatic Control, 51(6), 949-962. doi:10.1109/TAC.2006.876950
105. Kondacs, A. (2003). Biologically-inspired selfassembly of 2D shapes, using global-to-local compilation. In International Joint Conference on Artificial Intelligence, (pp. 633-638).
106. Kothari, N., Gummadi, R., Millstein, T., & Govindan, R. (2007). Reliable and efficient programming abstractions for wireless sensor networks. In Proceedings of the 2007 ACM SIGPLAN Conference on Programming Language Design and Implementation, (pp. 200-210). ACM.
107. Kulesza, U., Garcia, A., & Lucena, C. (2004). An aspect-oriented generative approach. In Companion to the 19th Annual ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA '04) (pp. 166-167). New York, NY: ACM.
108. Kulesza, U., Garcia, A., Lucena, C., & Alencar, P. (2005). A generative approach for multi-agent system development. Software Engineering for Multi-Agent Systems, III, 52-69. doi:10.1007/978-3-540-31846-0_4
109. Kwiatkowska, M., Norman, G., & Parker, D. (2011). PRISM 4.0: Verification of probabilistic real-time systems. In G. Gopalakrishnan & S. Qadeer (Eds.), Proc. 23rd International Conference on Computer Aided Verification (CAV'11), volume 6806 of LNCS, (pp. 585-591). Springer.
110. Lasser, C., Massar, J., Miney, J., & Dayton, L. (1988). Starlisp reference manual. Thinking Machines Corporation.
111. Levis, P., & Culler, D. (2002). Mate: a tiny virtual machine for sensor networks. In ACM Sigplan Notices, 37(10), 85-95.
112. Levis, P., Madden, S., Polastre, J., Szewczyk, R., Whitehouse, K., & Woo, A. ... Brewer, E. (2005). Tinyos: An operating system for sensor networks. In Ambient Intelligence, (pp. 115-148).
113. Li, S., Lin, Y., Son, S., Stankovic, J., & Wei, Y. (2004). Event detection services using data service middleware in distributed sensor networks. Telecommunication Systems, 26(2), 351-368. doi:10.1023/B:TELS.0000029046.79337.8f
114. Litovsky, I., Métivier, Y., & Zielonka, W. (1992). The power and the limitations of local computations on graphs. In Workshop on Graph-Theoretic Concepts in Computer Science (pp. 333-345).
115. Liu, J., Chu, M., Liu, J., Reich, J., & Zhao, F. (2003). State-centric programming for sensoractuator network systems. IEEE Pervasive Computing / IEEE Computer Society [and] IEEE Communications Society, 2(4), 50-62. doi:10.1109/MPRV.2003.1251169
116. Loo, B., Condie, T., Garofalakis, M., Gay, D., Hellerstein, J., & Maniatis, P. ... Stoica, I. (2006). Declarative networking: Language, execution and optimization. In Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data (pp. 97-108). ACM.
117. Lopes, N., Navarro, J., Rybalchenko, A., & Singh, A. (2010). Applying prolog to develop distributed systems. Theory and Practice of Logic Programming, 10(4-6), 691-707. doi:10.1017/S1471068410000360
118. Luke, S., Cioffi-Revilla, C., Panait, L., & Sullivan, K. (2004). Mason: A new multi-agent simulation toolkit. In Proceedings of the 2004 SwarmFest Workshop (pp. 1-8).
119. Macal, C., & North, M. (2010). Tutorial on agentbased modelling and simulation. Journal of Simulation, 4(3), 151-162. doi:10.1057/jos.2010.3
120. MacLennan, B. (1990). Continuous spatial automata. Technical Report Department of Computer Science Technical Report CS-90-121, University of Tennessee, Knoxville.
121. Madden, S. R., Szewczyk, R., Franklin, M. J., & Culler, D. (2002). Supporting aggregate queries over ad-hoc wireless sensor networks. InWorkshop on Mobile Computing and Systems Applications, (pp. 49 - 58).
122. Mallavarapu, A., Thomson, M., Ullian, B., & Gunawardena, J. (2009). Programming with models: Modularity and abstraction provide powerful capabilities for systems biology, Journal of the Royal Society Interface. 6(32), 257-270. doi:10.1098/rsif.2008.0205
123. Mamei, M., & Zambonelli, F. (2008). Programming pervasive and mobile computing applications: The TOTA approach. ACM Transactions on Software Engineering and Methodology, 18(4), 15:1-15:56.
124. Margolus, N. (1993). CAM-8: A computer architecture based on cellular automata. InAmerican Mathematical Society, 6(1) 167-187.
125. Martel, S., & Mohammadi, M. (2010). Using a swarm of self-propelled natural microrobots in the form of flagellated bacteria to perform complex micro-assembly tasks. InProceedings of the International Conference on Robotics and Automation (ICRA) (pp. 500-505).
126. Martinoli, A., Easton, K., & Agassounon, W. (2004). Modeling of swarm robotic systems: A case study in collaborative distributed manipulation. The International Journal of Robotics Research, 23(4), 415-436. doi:10.1177/0278364904042197
127. Martinoli, A., Ijspeert, A. J., & Mondada, F. (1999). Understanding collective aggregation mechanisms: From probabilistic modelling to experiments with real robots. Robotics & Autonomous Systems. Special Issue on Distributed Autonomous Robotic Systems, 29, 51-63. doi:10.1016/S0921-8890(99)00038-X
128. Mernik, M., Heering, J., & Sloane, A. (2005). When and how to develop domain-specific languages. ACM Computing Surveys, 37(4), 316-344. doi:10.1145/1118890.1118892
129. Michalakes, J. (1994). RSL: A parallel runtime system library for regular grid finite difference models using multiple nests. Technical Report ANL/MCS-TM-197, Argonne National Laboratory.
130. Michalakes, J. (1997). FLIC: A translator for same-source parallel implementation of regular grid applications. Technical Report ANL/MCS-TM-223, Argonne National Laboratory.
131. Milner, R. (1999). Communicating and mobile systems: The Pi-calculus. Cambridge University Press.
132. Minar, N., Burkhart, R., Langton, C., & Askenazi, M. (1996). The swarm simulation system, a toolkit for building multi-agent simulations. Technical Report Working Paper 96-06-042, Santa Fe Institute.
133. Mirschel, S., Steinmetz, K., Rempel, M., Ginkel, M., & Gilles, E. D. (2009). Promot: Modular modeling for systems biology. Bioinformatics (Oxford England), 25(5), 687-689. doi:10.1093/bioinformatics/btp029
134. Mishra, M., Callahan, T., Chelcea, T., Venkataramani, G., Budiu, M., & Goldstein, S. (2006). Tartan: Evaluating spatial computation for whole program execution. InProceedings of 12th ACM International Conference on Architecture Support for Programming Languages and Operating Systems (ASPLOS 2006) (pp. 163-174).
135. MIT Media Lab and Schellar Teacher Education Program. (2011). Starlogo. Retrieved from http://education.mit.edu/starlogo/
136. Proto, M. I. T. (Retrieved November 22, 2010). MIT Proto. Retrieved from http://proto.bbn.com/
137. Montagna, S., Viroli, M., Risoldi, M., Pianini, D., & Di Marzo Serugendo, G. (2011). Self-organising pervasive ecosystems: A crowd evacuation example. In 3rd International Workshop on Software Engineering for Resilient Systems, volume 6968 of Lecture Notes in Computer Science, (pp. 115-129). Springer.
138. Moss, S., Gaylard, H., Wallis, S., & Edmonds, B. (1998). SDML: A multi-agent language for organizational modelling. Computational & Mathematical Organization Theory, 4, 43-69. doi:10.1023/A:1009600530279
139. Mottola, L., & Picco, G. (2006). Logical neighborhoods: A programming abstraction for wireless sensor networks (pp. 150-168). Distributed Computing in Sensor Systems. doi:10.1007/11776178_10
140. Mottola, L., & Picco, G. (2011). Programming wireless sensor networks: Fundamental concepts and state of the art. ACM Computing Surveys, 43(3), 19-75. doi:10.1145/1922649.1922656
141. MPI2. (2009). MPI: A message-passing interface standard version 2.2. Message Passing Interface Forum.
142. Mucci, C., Campi, F., Brunelli, C., & Nurmi, J. (2007). Programming tools for reconfigurable processors. In Nurmi, J. (Ed.), System-On-Chip Computing for ASICs and FPGAs on Processor Design (pp. 427-446). Springer.
143. Myers, C., Barker, N., Jones, K., Kuwahara, H., Madsen, C., and Nguyen, N. (2009). iBioSim: A tool for the analysis and design of genetic circuits. Bioinformatics (Oxford, England), 25, 2848-2849. doi:10.1093/bioinformatics/btp457
144. Nagpal, R. (2001). Programmable self-assembly: Constructing global shape using biologicallyinspired local interactions and origami mathematics. PhD thesis, MIT.
145. Newton, R., Morrisett, G., & Welsh, M. (2007). The regiment macroprogramming system. In Proceedings of the 6th International Conference on Information Processing in Sensor Networks (pp. 489-498). ACM.
146. Newton, R., & Welsh, M. (2004). Region streams: Functional macroprogramming for sensor networks. In First International Workshop on Data Management for Sensor Networks (DMSN) (pp. 78-87).
147. Nguyen, D. N., Usbeck, K., Mongan, W. M., Cannon, C. T., Lass, R. N., Salvage, J., & Regli, W. C. (2010). A methodology for developing an agent systems reference architecture. In 11th International Workshop on Agent-Oriented Software Engineering (pp. 177-188).
148. North, M., Howe, T., Collier, N., & Vos, J. (2007). A declarative model assembly infrastructure for verification and validation. In The First World Congress on Advancing Social Simulation (pp. 129-140). Springer Japan.
149. th National Conference on Artificial Intelligence (pp. 3-17). AAAI Press.
150. Open, C. L. (2011). The OpenCL specification, version 1.2. Khronos OpenCL Working Group.
151. Open, M. P. (2011). OpenMP application program interface version 3.1. OpenMP Architecture Review Board.
152. Palmer, J., & Steele, J. G. L. (1992). Connection machine model cm-5 system overview. In Fourth Symposium on the Frontiers of Massively Parallel Computation (pp. 474-483). IEEE Press.
153. Pathak, A., Mottola, L., Bakshi, A., Prasanna, V., & Picco, G. (2007). Expressing sensor network interaction patterns using data-driven macroprogramming. In Proceedings of the Fifth IEEE International Conference on Pervasive Computing and Communications Workshops (pp. 255-260). IEEE Computer Society.
154. Paun, G. (2000). Computing with membranes. Journal of Computer and System Sciences, 61(1), 108-143. doi:10.1006/jcss.1999.1693
155. Paun, G. (2002). Membrane computing: An introduction. Springer.
156. st International Conference on Advanced Networking and Applications (AINA '07) (pp. 370-377).
157. Pedersen, M., & Phillips, A. (2009). Towards programming languages for genetic engineering of living cells. Journal of the Royal Society Interface, 6, S437-S450. doi:10.1098/rsif.2008.0516.focus
158. Pierce, B. C., & Turner, D. N. (2000). Pict: a programming language based on the pi-calculus. In Plotkin, G. D., Stirling, C., & Tofte, M. (Eds.), Proof, language, and interaction, essays in honour of Robin Milner (pp. 455-494). The MIT Press
159. Pierro, A. D., Hankin, C., & Wiklicky, H. (2005). Continuous-time probabilistic klaim. Electronic Notes in Theoretical Computer Science, 128(5), 27-38. doi:10.1016/j.entcs.2004.11.040
160. Pokahr, A., Braubach, L., & Lamersdorf, W. (2003). Jadex: Implementing a BDI-infrastructure for jade agents. EXP-in Search of Innovation, 3(3), 76-85.
161. Pressey, C. (Retrieved Feb 20, 2012). The alpaca meta-language. Retrieved from http://catseye.tc/projects/alpaca/
162. Priami, C. (1995). Stochastic pi-calculus. The Computer Journal, 38(7), 578-589. doi:10.1093/comjnl/38.7.578
163. Prorok, A., Correll, N., & Martinoli, A. (2011). Multi-level spatial models for swarm-robotic systems. The International Journal of Robotics Research. Special Issue on Stochasticity in Robotics and Biological Systems, 30(5), 574-589.
164. Prusinkiewicz, P., & Lindenmayer, A. (1990). The algorithmic beauty of plants. New York, NY: Springer-Verlag. doi:10.1007/978-1-4613-8476-2
165. Raimbault, F., & Lavenier, D. (1993). Relacs for systolic programming. InInternational Conference on Application-Specific Array Processors (pp. 132-135).
166. Rao, A., & Georgeff, M. (1995). BDI agents: From theory to practice. In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95) (pp. 312-319).
167. Regli, W. C., Mayk, I., Dugan, C. J., Kopena, J. B., Lass, R. N., & Modi, P. J. (2009). Development and specification of a reference model for agentbased systems. Transactions on Systems Man and Cybernetics, 39(Part C), 572-596. doi:10.1109/TSMCC.2009.2020507
168. th Midwest Symposium on Circuits and Systems (pp. 712-715).
169. Repast Team. (2011). The repast suite. Retrieved from http://repast.sourceforge.net/index.html
170. Resnick, M. (1996). Starlogo: An environment for decentralized modeling and decentralized thinking. In Conference Companion on Human Factors in Computing Systems: Common Ground (pp. 11-12). ACM.
171. Rus, D., Butler, Z. J., Kotay, K., & Vona, M. (2002). Self-reconfiguring robots. Communications of the ACM, 45(3), 39-45. doi:10.1145/504729.504752
172. Rus, D., & Vona, M. (2001). Crystalline robots: Self-reconfiguration with compressible unit modules. Autonomous Robots, 10(1), 107-124. doi:10.1023/A:1026504804984
173. Russell, S., Norvig, P., Canny, J., Malik, J., & Edwards, D. (1995). Artificial intelligence: A modern approach. Englewood Cliffs, NJ: Prentice Hall.
174. Saraswat, V., Bloom, B., Peshansky, I., Tardieu, O., & Grove, D. (2012). X10 language specification version 2.2. Yorktown Heights, NY: IBM.
175. Schultz, U., Bordignon, M., Christensen, D., & Stoy, K. (2008). Spatial computing with labels. In Spatial Computing Workshop (pp. 326 - 331).
176. Schultz, U. P., Christensen, D. J., & Stoy, K. (2007). A domain-specific language for programming self-reconfigurable robots. In Workshop on Automatic Program Generation for Embedded Systems (APGES) (pp. 28-36).
177. Shen, C., Srisathapornphat, C., & Jaikaeo, C. (2001). Sensor information networking architecture and applications. IEEE Personal Communications, 8(4), 52-59. doi:10.1109/98.944004
178. Shen, W.-M., Will, P., Galstyan, A., & Chuong, C. (2004). Hormone-inspired self-organization and distributed control of robotic swarms. Autonomous Robots, 17(1), 93-105. doi:10.1023/B:AURO.0000032940.08116.f1
179. Sklar, E. (2007). Netlogo, a multi-agent simulation environment. Artificial Life, 13(3), 303-311. doi:10.1162/artl.2007.13.3.303
180. Smith, L. P., Bergmann, F. T., Chandran, D., & Sauro, H. M. (2009). Antimony: A modular model definition language. Bioinformatics (Oxford England), 25(18), 2452-2454. doi:10.1093/bio-informatics/btp401
181. Spezzano, G., & Talia, D. (1997). A high-level cellular programming model for massively parallel processing. In 2nd Int'l Workshop on High-Level Programming Models and Supportive Environments (HIPS'97) (pp. 55-63).
182. Stoy, K., & Nagpal, R. (2004). Self-repair through scale independent self-reconfiguration. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2062-2067).
183. Sugihara, R., & Gupta, R. (2008). Programming models for sensor networks: A survey. ACM Transactions on Sensor Networks, 4(2), 8:1-8:29.
184. Swanson, S., Schwerin, A., Mercaldi, M., Petersen, A., Putnam, A., Michelson, K., ... Eggers, S. J. (2007). The wavescalar architecture. ACM Transactions on Computing Systems, 25(2), 4:1-4:54.
185. Szymanski, M., & Woern, H. (2007). JaMOS - A MDL2ε based operating system for swarm micro robotics. In Proceedings of the 2007 IEEE Swarm Intelligence Symposium (pp. 324 - 331).
186. Taylor, M. B., Kim, J., Miller, J., Wentzlaff, D., Ghodrat, F., & Greenwald, B. (2002). The raw microprocessor: A computational fabric for software circuits and general purpose programs. IEEE Micro, 22(2), 25-35. doi:10.1109/MM.2002.997877
187. Telecom Italia Lab. (2011). JADE - Java Agent DEvelopment framework. Retrieved from http://jade.tilab.com/
188. The Klavins Lab. (2012). Gro: The cell programming language. University of Washington. Retrieved from http://depts.washington.edu/soslab/gro/
189. Thies, W., Karczmarek, M., Gordon, M., Maze, D., Wong, J., Hoffmann, H., & Brown, M. (2001). Streamit: A compiler for streaming applications. Technical Report MIT-LCS Technical Memo TM-622, Massachusetts Institute of Technology.
190. Tobis, M. (2005). Pynsol: Objects as scaffolding. Computing in Science & Engineering, 7(4), 84-91. doi:10.1109/MCSE.2005.78
191. Toffoli, T., & Margolus, N. (1987). Cellular Automata Machines: A new environment for modeling. MIT Press.
192. Trencansky, I., & Cervenka, R. (2005). Agent modeling language (AML): A comprehensive approach to modeling MAS. Informatica Ljubljana, 29(4), 391.
193. University of Michigan Center for the Study of Complex Systems. (2011). Swarm development wiki. Retrieved from http://www.swarm.org/index.php/Main_Page
194. Usbeck, K., & Beal, J. (2011). An agent framework for agent societies. In Proceedings of the Compilation of the Co-Located Workshops on DSM'11, TMC'11, AGERE!'11 at Systems, Programming, Languages and Applications: Software for Humanity (pp. 201-212).
195. Viroli, M., Casadei, M., Montagna, S., & Zambonelli, F. (2011a). Spatial coordination of pervasive services through chemical-inspired tuple spaces. ACM Transactions on Autonomous and Adaptive Systems, 6(2), 14:1-14:24.
196. Viroli, M., Nardini, E., Castelli, G., Mamei, M., & Zambonelli, F. (2011b). A coordination approach to spatially-situated pervasive service ecosystems. In G. Fortino, A. Garro, L. Palopoli, W. Russo, & G. Spezzano (Eds.), WOA 2011 - XII Workshop Nazionale "Dagli Oggetti agli Agenti", volume 741 of CEUR Workshop Proceedings, (pp. 19-27). Sun SITE Central Europe, RWTH Aachen University.
197. Walter, J., Welch, J., & Amato, N. (2004). Distributed reconfiguration of metamorphic robot chains. Distributed Computing, 17, 171-189. doi:10.1007/s00446-003-0103-y
198. Weiss, R. (2001). Cellular computation and communications using engineered genetic regular networks. PhD thesis, MIT.
199. Welsh, M., & Mainland, G. (2004). Programming sensor networks using abstract regions. In Proceedings of the First USENIX/ACM Symposium on Networked Systems Design and Implementation (NSDI '04) (pp. 3-17).
200. Werfel, J. (2006). Anthills built to order: Automating construction with artificial swarms. PhD thesis. Cambridge, MA: MIT Press.
201. Werfel, J., Bar-Yam, Y., & Nagpal, R. (2005). Building patterned structures with robot swarms. In International Joint Conference on Artificial Intelligence (pp. 1495-1502).
202. Werfel, J., & Nagpal, R. (2007). Collective construction of environmentally-adaptive structures. In 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2007) (pp. 2345-2352). IEEE.
203. Whitehouse, K., Sharp, C., Brewer, E., & Culler, D. (2004). Hood: A neighborhood abstraction for sensor networks. In Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services (pp. 99-110). ACM Press.
204. Wilensky, U. (2011). Netlogo. Retrieved from http://ccl.northwestern.edu/netlogo/
205. Yamins, D. (2007). A theory of local-to-global algorithms for one-dimensional spatial multiagent systems. PhD thesis, Harvard, Cambridge, MA, USA.
206. Yang, C., Wu, H., Huang, Q., Li, Z., & Li, J. (2011). Using spatial principles to optimize distributed computing for enabling the physical science discoveries. [PNAS]. Proceedings of the National Academy of Sciences of the United States of America, 108(14), 5498-5503. doi:10.1073/pnas.0909315108
207. Yao, Y., & Gehrke, J. (2002). The cougar approach to in-network query processing in sensor networks. SIGMOD Record, 31(3), 9-18. doi:10.1145/601858.601861
208. Yim, M., Shen, W., Salemi, B., Rus, D., Moll, M., & Lipson, H. (2007). Modular self-reconfigurable robot systems: Grand challenges of robotics. Robotics & Automation Magazine, IEEE, 14(1), 43-52. doi:10.1109/MRA.2007.339623
209. Zambonelli, F., & Viroli, M. (2011). A survey on nature-inspired metaphors for pervasive service ecosystems. International Journal of Pervasive Computing and Communications, 7(3), 186-204. doi:10.1108/17427371111172997
210. Zimmermann, H. (1980). OSI reference model-the ISO model of architecture for open systems interconnection. IEEE Transactions on Communications, 28(4), 425-432. doi:10.1109/TCOM.1980.1094702