Integrating BDI Agents with Agent-Based Simulation Platforms

Autonomous Agents and Multi-Agent Systems

Volumn 30, Issue 6, 2016, Pages 1050-1071

  Singh, Dhirendra ^a   Padgham, Lin ^a   Logan, Brian ^b  

^a RMIT UNIVERSITY   (Australia)

^b UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

Agent based modelling; BDI; Integration; Simulation

Indexed keywords

AUTONOMOUS AGENTS; COMPUTATIONAL METHODS; DECISION MAKING; INTEGRATION;

AGENT BASED SIMULATION; AGENT-BASED MODEL; AGENT-BASED MODELLING; BELIEF-DESIRE-INTENTIONS; COGNITIVE AGENTS; OPEN SOURCES; SIMULATION; TIME STEPPED;

INTELLIGENT AGENTS;

EID: 84961202953     PISSN: 13872532     EISSN: 15737454     Source Type: Journal    
DOI: 10.1007/s10458-016-9332-x     Document Type: Article

References (60)

1. Axelrod, R. M. (1997). The complexity of cooperation: Agent-based models of competition and collaboration. Princeton: Princeton Univeristy Press.
2. Balke, T., & Gilbert, N. (2014). How do agents make decisions? A survey. Journal of Artificial Societies and Social Simulation (JASSS), 17(4), 13.
3. Balmer, M., Rieser, M., Meister, K., Charypar, D., Lefebvre, N., Nagel, K., Axhausen, K. (2009). MATSim-T: Architecture and simulation times. Multi-agent Systems for Traffic and Transportation Engineering, 57–78.
4. Behrens, T. M., Dastani, M., Dix, J., Hübner, J., Köster, M., Novák, P., et al. (2012). The multi-agent programming contest. AI Magazine, 33(4), 111–113.
5. Benfield, S. S., Hendrickson, J., & Galanti, D. (2006). Making a strong business case for multiagent technology. Autonomous agents and multi-agent systems (AAMAS) (pp. 10–15). Hakodate: ACM Press.
6. Boissier, O., Bordini, R. H., Hübner, J. F., Ricci, A., & Santi, A. (2013). Multi-agent oriented programming with JaCaMo. Science of Computer Programming, 78(6), 747–761.
7. Bordini, R.H., Hübner, J.F. (2005). BDI agent programming in AgentSpeak using Jason. In: International Workshop on Computational Logic in Multi-Agent Systems (CLIMA) (pp. 143–164). London, UK.
8. Bordini, R. H., & Hübner, J. F. (2009). Agent-based simulation using BDI programming in Jason. Multi-agent systems: simulation and applications (pp. 451–471). Boca Raton: CRC Press.
9. Bordini, R.H., Hübner, J.F., Wooldridge, M. (2007) Programming multi-agent Systems in AgentSpeak using Jason. Wiley series in agent technology. Hoboken: Wiley. ISBN: 0470029005
10. Bratman, M. E. (1987). Intentions, plans, and practical reason. Massachusetts: Harvard University Press.
11. Braubach, L., Pokahr, A., & Lamersdorf, W. (2005). Jadex: A BDI agent system combining middleware and reasoning. Software agent-based applications, platforms and development kits (pp. 143–168). Boston: Springer.
12. Busetta, P., Rönnquist, R., Hodgson, A., Lucas, A. (1998). JACK intelligent agents - components for intelligent agents in Java. Technical report, AOS Pty. Ltd, Melbourne, Australia.
13. Dastani, M. (2008). 2APL: A practical agent programming language. Autonomous Agents and Multi-Agent Systems, 16(3), 214–248.
14. Dennett, D. C. (1987). The intentional stance. Cambridge: MIT Press.
15. Dignum, V., Vázquez-Salceda, J., Dignum, F. (2004). OMNI: Introducing social structure, norms and ontologies into agent organizations. In Programming multiagent systems languages, frameworks, techniques and tools workshop (PROMAS). (pp. 181–198). Selected revised and invited papers.
16. Epstein, J. (2006). Generative social science—studies in agent-based computational modeling. Princeton: Princeton University Press.
17. Ferber, J. (1999). Multi-Agent Systems. Boston: Addison Wesley Longman.
18. GAMS Development Corporation: General algebraic modeling system (gams) website. Retrieved from March 20, 2015 from http://www.gams.com/.
19. Geard, N., McCaw, J. M., Dorin, A., Korb, K. B., & McVernon, J. (2013). Synthetic population dynamics: A model of household demography. Journal of Artificial Societies and Social Simulation, 16(1), 8.
20. Geard, N., Singh, D., McVernon, J., Padgham, L. (2013). A model of parental decision making and behaviour about childhood vaccination. In Epidemics 4: Fourth international conference on infectious disease dynamics (pp. 19–22). Amsterdam.
21. Georgeff, M., Ingrand, F. (1989). Decision making in an embedded reasoning system. In: International joint conference on artificial intelligence (IJCAI) (pp. 972–978). Detroit.
22. Gilbert, N., & Troitzsch, K. (2005). Simulation for the social scientist. New York: McGraw-Hill International.
23. Hindriks, K. V. (2009). Programming rational agents in GOAL. Multi-agent programming: languages, tools and applications (pp. 119–157). New York: Springer.
24. IEEE (2000). IEEE Standard for modeling and simulation (M&S) High Level Architecture (HLA)—Framework and rules. IEEE Standard No.: 1516-2000. IEEE, Piscataway
25. Iftekhar, M., Hailu, A., & Lindner, R. (2014). Does it pay to increase competition in combinatorial conservation auctions? Canadian Journal of Agricultural Economics/Revue canadienne d’agroeconomie, 62(3), 411–433.
26. Jarvis, D., Jarvis, J., Rnnquist, R., & Jain, L. C. (2013). Multiagent systems and applications, development using the GORITE BDI framework. Intelligent Systems Reference Library (Vol. 46). New York: Springer.
27. Kaminka, G. A., Veloso, M. M., Schaffer, S., Sollitto, C., Adobbati, R., Marshall, A. N., et al. (2002). GameBots: A flexible test bed for multiagent team research. Communications of the ACM, 45(1), 43–45.
28. Kitano, H., Asada, M., Kuniyoshi, Y., Noda, I., Osawa, E. (1997). RoboCup: The robot world cup initiative. In First international conference on autonomous agents (Agents’97) (pp. 340–347). Marina del Rey.
29. Kitano, H., & Tadokoro, S. (2001). Robocup rescue: A grand challenge for multiagent and intelligent systems. AI Magazine, 22(1), 39–52.
30. Kuhl, F., Weatherly, R., & Dahmann, J. (1999). Creating computer simulation systems: An introduction to the high level architecture. Upper Saddle River: Prentice Hall.
31. Lees, M., Logan, B., & Theodoropoulos, G. (2007). Distributed simulation of agent-based systems with HLA. ACM Transactions on Modeling and Computer Simulation, 17(3), 11.
32. Minson, R., & Theodoropoulos, G. K. (2008). Distributing repast agent-based simulations with hla. Concurrency and Computation: Practice and Experience, 20(10), 1225–1256.
33. Mittal, S., & Douglass, S. A. (2011). Net-centric ACT-R-based cognitive architecture with DEVS unified process. In Symposium on theory of modeling & simulation: DEVS integrative M&S symposium, TMS-DEVS’11 (pp. 34–44). Boston.
34. North, M. J., Howe, T. R., Collier, N. T., & Vos, J. R. (2007). Advancing social simulation: The first world congress. A declarative model assembly infrastructure for verification and validation (pp. 129–140). Tokyo: Springer.
35. van Oijen, J. (2014). Cognitive agents in virtual worlds: A middleware design approach. Ph.D. thesis, Utrecht University.
36. Padgham, L., Horne, R., Singh, D., & Moore, T. (2014). Planning for sandbagging as a response to flooding: A tool and case study. Australian Journal of Emergency Management (AJEM), 29, 26–31.
37. Padgham, L., Nagel, K., Singh, D., Chen, Q. (2014). Integrating bdi agents into a matsim simulation. Frontiers in Artificial Intelligence and Applications 263(ECAI 2014), 681–686
38. Padgham, L., Scerri, D., Jayatilleke, G.B., Hickmott, S.L. (2011). Integrating BDI reasoning into agent based modeling and simulation. In: Winter simulation conference (WSC) (pp. 345–356).
39. Rao, A., Georgeff, M. (1991). Modeling rational agents within a BDI-architecture. In Principles of knowledge representation and reasoning (KR) (pp. 473–484). Cambridge, MA.
40. Rao, A. S. (1996). AgentSpeak (L): BDI agents speak out in a logical computable language. Agents breaking away (pp. 42–55). Berlin: Springer.
41. Rao, A.S., Georgeff, M.P. (1995). BDI agents: From theory to practice. In International conference on multi-agent systems (ICMAS) (pp. 312–319). San Francisco.
42. Reynolds, C. W. (1987). Flocks, herds and schools: A distributed behavioral model. In 14th Annual conference on computer graphics and interactive techniques, SIGGRAPH ’87 (pp. 25–34). New York.
43. Russell, S. J., & Norvig, P. (2003). Artificial intelligence: A modern approach (2nd ed.). Upper Saddle River: Pearson Education.
44. Sakellariou, I., Kefalas, P., & Stamatopoulou, I. (2008). Enhancing NetLogo to simulate BDI communicating agents. Artificial intelligence: Theories, models and applications (Vol. 5138, pp. 263–275)., Lecture Notes in Computer Science Springer: Berlin.
45. Sardiña, S., & Padgham, L. (2011). A BDI agent programming language with failure handling, declarative goals, and planning. Autonomous Agents and Multi-Agent Systems, 23(1), 18–70.
46. Scerri, D., Hickmott, S., Bosomworth, K., & Padgham, L. (2012). Using modular simulation and agent based modelling to explore emergency management scenarios. Australian Journal of Emergency Management (AJEM), 27, 44–48.
47. Shendarkar, A., Vasudevan, K., Lee, S., Son, Y.J. (2006). Crowd simulation for emergency response using BDI agent based on virtual reality. In Winter simulation conference (WSC) (pp. 545–553). Monterey.
48. Sierhuis, M., Clancey, W. J., & van Hoof, R. J. J. (2007). Brahms: A multiagent modelling and simulation environment for work processes and practices. International Journal of Simulation and Process Modelling, 3(3), 134–152.
49. Singh, D., Padgham, L. (2015). Community evacuation planning for bushfires using agent-based simulation (demonstration). In Autonomous agents and multi-agent systems (AAMAS) (pp. 1903–1904). Istanbul.
50. Singh, D., Sardina, S., Padgham, L., James, G. (2011). Integrating learning into a BDI agent for environments with changing dynamics. In International joint conference on artificial intelligence (IJCAI) (pp. 2525–2530). Barcelona.
51. Sloman, A., & Poli, R. (1996). SIM AGENT: A toolkit for exploring agent designs. Intelligent agents II: Agent theories architectures and languages (ATAL-95) (pp. 392–407). New York: Springer.
52. Tambe, M. (1997). Towards flexible teamwork. Journal of Artificial Intelligence Research, 7, 83–124.
53. Tambe, M., Johnson, W. L., Jones, R. M., Koss, F. V., Laird, J. E., Rosenbloom, P. S., et al. (1995). Intelligent agents for interactive simulation environments. AI Magazine, 16(1), 15–39.
54. Taylor, G., Frederiksen, R., III, R.R.V., Waltz, E. (2004). Agent-based simulation of geo-political conflict. In: Conference on innovative applications of artificial intelligence (IAAI) (pp. 884–891). San Jose.
55. Tidhar, G., Heinze, C., & Selvestrel, M. C. (1998). Flying together: Modelling air mission teams. Applied Intelligence, 8(3), 195–218.
56. Tisue, S., Wilensky, U. (2004). Netlogo: A simple environment for modeling complexity. In International conference on complex systems (ICCS) (pp. 16–21). Boston.
57. Tolhurst, K., Shields, B., & Chong, D. (2008). Phoenix: development and application of a bushfire risk management tool. Australian Journal of Emergency Management (AJEM), 23(4), 47–54.
58. Winikoff, M. (2005). JACK intelligent agents: An industrial strength platform. Multi-agent programming: languages, platforms and applications, multiagent systems, artificial societies, and simulated organizations (Vol. 15, pp. 175–193). New York: Springer.
59. Zeigler, B. P., Praehofer, H., & Kim, T. G. (2000). Theory of modeling and simulation (2nd ed.). Cambridge: Academic Press.
60. Zhang, M., Verbraeck, A. (2014). A composable PRS-based agent meta-model for multi-agent simulation using the DEVS framework. In Symposium on Agent Directed Simulation, ADS’14 (pp. 1:1–1:8).