A.L. Yalovets, Dr Sc. (Eng.),
Institute of Program Systems, NAS of Ukraine
5 Bldg, 40 Acad. Glushkov Ave, Kyiv, 03187, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Èlektron. model. 2018, 40(1):03-16


The problem of constructing taxonomy of autonomous agents has been investigated. The most well-known taxonomy of autonomous agents proposed by S. Franklin and A. Graesser has been analyzed and the contradictions in it have been considered. Based on this analysis results a new taxonomy of autonomous agents is proposed. This taxonomy realizes natural classification of autonomous agents and takes into account the current state of their research. The classes and subclasses of autonomous agents that are represented in the taxonomy are defined. Three main classes of computer agents are compared and the main differences between them are distinguished.


taxonomy, classification, autonomous agents, software agents, modeling agents, simulation agents. 


1. Yalovets, A.L. (2013), “To problem definition on prosecuting in the plane”, Problemy programuvannya, no. 2, pp. 95-100.
2. Yalovets, A.L. (2013), “About one method of persecution on a plane”, Problemy programuvannya, no. 3, pp. 117-124.
3. Yalovets, A.L. (2013), “About the method of the nearest point as a method of strategies management of pursuit/escape of agents”, Problemy programuvannya, no. 4, pp. 94-99.
4. Yalovets, A.L. (2014), “Methods of modeling the behavior of agents in multi-agent system Navigation", Problemy programuvannya, no. 2-3, pp. 212-220.
5. Yalovets, A.L. (2014), “The problem of the formation of groups of agents in the tasks of pursuit/escape on a plane”, Problemy programuvannya, no. 1, pp. 108-118.
6. Yalovets, A.L. (2015), “The problem of modelling of maneuvering of agents in the tasks of pursuit/escape on a plane”, Problemy programuvannya, no. 2, pp. 86-100.
7. Yalovets, A.L. (2017), “The architecture and functionality of the multi-agent system Navigation”, Problemy programuvannya, no. 1, pp. 83-96.
8. Yalovets, A.L., Kondraschenko, V.Ya. and Aristov, V.V. (2014), 57880 Certificate of registration of copy-right in a product. Computer program — “Multi-agent systems «Navigation» version 2.5”. The State Service of Intellectual Property of Ukraine.
9. Franklin, S. and Graesser, A. (1996), Is it an agent, or just a program?: A taxonomy for autonomous agents, Proceedings of Workshop Intelligent Agents III : Agent Theories, Architectures, and Languages (ECAI’96), Springer, Budapest, Hungary, pp. 21-35.
10. Sanchez, J.A. (1997), A taxonomy of agents. Technical report ICT-97-1, Interactive and Cooperative Technologies Lab, Department of Computer Systems Engineering, Universidad de las Americas-Puebla, Mexico.
11. Huang, Z., Eliens, A., van Ballegooij, A. and de Bra, P. (2000), A taxonomy of web agents, Proceedings of the 11th International Workshop on Database and Expert Systems Applications, London, UK, pp. 765-769.
12. Coninx, K. and Holvoet, T. A (2014), A microscopic traffic simulation platform for coordinated charging of electric vehicles, Proceedings of the 12th International Conference “Advances in Practical Applications of Heterogeneous Multi-Agent Systems” (PAAMS 2014), Springer, Salamanca, Spain, pp. 323-326.
13. Garcia-Magarino, I. (2014), Practical multi-agent system application for simulation of tourists in Madrid routes with INGENIAS, Proceedings of the 12th International Conference “Advances in Practical Applications of Heterogeneous Multi-Agent Systems” (PAAMS 2014), Springer, Salamanca, Spain, pp. 122-133.
14. Hajinasab, B., Davidsson, P., Persson, J.A. and Holmgren, J. (2016), Towards an agent-based model of passenger transportation, Proceedings of International Workshop “Multi-Agent-Based Simulation XVI” (MABS 2015), Springer, Istanbul, Turkey, pp. 132-145.
15. Hassan, S., Antunes, L. and Pavón, J. (2010), Mentat: a data-driven agent-based simulation of social values evolution, Proceedings of International Workshop “Multi-Agent-Based Simulation X” (MABS 2009), Springer, Budapest, Hungary, pp. 135-146.
16. Henein, C.M. and White, T. (2005), Agent-based modeling of forces in crowds, Proceedings of Joint Workshop “Multi-Agent and Multi-Agent-Based Simulation” (MABS 2004), Springer, New York, USA, pp. 173-184.
17. Jordan, R., Birkin, M. and Evans, A. (2011), Agent-based simulation modeling of housing choice and urban regeneration policy, Proceedings of International Workshop “Multi-Agent-Based Simulation XI” (MABS 2010), Springer, Toronto, Canada, pp. 152-166.
18. Molina, M., Martin, J. and Carrasco, S. (2014), An agent-based approach for the design of the future European air traffic management system, Proceedings of the 12th International Conference “Advances in Practical Applications of Heterogeneous Multi-Agent Systems” (PAAMS 2014), Springer, Salamanca, Spain, pp. 359-362.
19. Monga, R. and Karlapalem, K. (2009), MASFMMS: Multi-agent systems framework for malware modeling and simulation, Proceedings of International Workshop “Multi-Agent-Based Simulation IX” (MABS 2008), Springer, Estoril, Portugal, pp. 97-109.
20. Niwa, T., Okaya, M. and Takahashi, T. (2015), TENDENKO: Agent-based evacuation drill and emergency planning system, Proceedings of International Workshop “Multi-Agent-Based Simulation XV” (MABS 2014), Springer, Paris, France, pp. 167-179.
21. Pezzulo, G. and Calvi, G. (2005), Designing and implementing MABS in AKIRA, Proceedings of Joint Workshop “Multi-Agent and Multi-Agent-Based Simulation” (MABS 2004), Springer, New York, USA, pp. 49-64.
22. Vanëk, O., Jakob, M., Hrstka, O. and Pëchoucëk, M. (2012), Using multi-agent simulation to improve the security of maritime transit, Proceedings of International Workshop “Multi-Agent-Based Simulation XII” (MABS 2011), Springer, Taipei, Taiwan, pp. 44-58.
23. Werlang, P., Fagundes, M.Q., Adamatti, D.F. and et al. (2014), Multi-agent-based simulation of mycobacterium tuberculosis growth, Proceedings of International Workshop “Multi-Agent-Based Simulation XIV” (MABS 2013), Springer, Saint Paul, USA, pp. 131-142.
24. Georgakarakou, C.E. and Economides, A.A. (2009), Software agent Technology: An overview, Software applications: concepts, methodologies, tools, and applications, Edited by Tiako P.F., IGI Global, pp. 128-151.
25. Macal, C.M. and North, M.J. (2014), Tutorial on agent-based modeling and simulation, Agentbased modeling and simulation, Edited by Taylor S.J.E., Palgrave MacMillan, pp. 11-31.
26. Meyers, R.A., editor (2009), Encyclopedia of complexity and systems science, Springer.
27. Weiss, G., editor (1999), Multiagent systems: a modern approach to distributed artificial intelligence, The MIT Press, Massachusetts, USA.
28. Hadzic, M., Wongthongtham, P., Dillon, T. and Chang, E. (2009), Ontology-based multiagent systems, Springer.
29. Padgham, L. and Winikoff, M. (2004), Developing intelligent agent systems. A practical guide, John Wiley & Sons Ltd.
30. Wooldridge, M. (2002), An introduction to multiagent systems, JohnWiley & Sons, Ltd.
31. Wooldridge, M. and Jennings, N.R. (1995), Intelligent agents: Theory and practice, The Knowledge Engineering Review, Vol. 10, no. 2, pp. 115-152.
32. Available at: https://www.collinsdictionary.com/dictionary/english/entity
33. Available at: https://en.wikipedia.org/wiki/Entity
34. Wooldridge, M. (2000), Reasoning about rational agents, The MIT Press, Massachusetts, USA.
35. Hexmoore, H., Castelfranchi, C. and Falcone, R., eds (2003), Agent autonomy, Springer Science + Business Media, LLC.
36. Nickles, M., Rovatsos, M. and Weiss, G. eds (2005), Agents and computational autonomy. Potential, risks and solutions, Springer Science + Business Media, Inc.
37. Mele, A.R. (1995), Autonomous agents. From self-control to autonomy, Oxford University Press, Oxford, USA.
38. Leitno, P. and Karnouskos, S., eds (2015), Industrial agents. Emerging applications of software agents in industry, Elsevier.
39. Odell, J. (2007), Agent technology: What is it and why do we care? Enterprise Architecture Advisory Service Executive Report. Cutter Consortium, Vol. 10, no. 3, pp. 1-25.
40. Weyns, D., Michel, F., Van Dyke Parunak, H. et al. (2015), Agent environments for multiagent systems – a research roadmap, Proceedings of the 4th International Workshop “Agent Environments for Multi-Agent Systems” (E4MAS 2014), Springer, Paris, France, pp. 3-21.
41. Weyns, D., Omicini, A. and Odell, J. (2007), Environment as a first class abstraction in multiagent systems, Vol. 14, Iss. 1, pp. 5-30.
42. Russell, S. and Norvig, P. (2007), Iskusstvennyi intellect: Sovremennyi podkhod [Artificial intelligence: Modern approach], 2nd ed., Transl. from English, Izd. dom “Vilyams”, Moscow, Russia.
43. Shatalkin, A.I. (2012), Takcsonomiya. Osnovy, printsipy i pravila [Taxonomy. Grounds, principles and rules], Tovarishchestvo nauchnykh izdaniy KMK, Moscow, Russia.
44. Yilmaz, L. and _ren, T. eds (2009), Agent-directed simulation and systems engineering, WILEY-VCH Verlag GmbH & Co.
45. Kondakov, N.I. (1976), Logicheskii slovar spravochnik [Logical reference-dictionary], Nauka, Moscow, USSR.
46. Bocharov, V.A. and Markin, V.I. (1998), Osnovy logiki [The basics of logic], INFRA-M, Moscow, USSR.
47. H`ppner, S. (2003), An agents’ definition framework and a methodology for deriving agents’ taxonomies, Proceedings of the 26th Annual German Conference on AI, Hamburg, Germany, pp. 618-632.
48. Poole, D.L. and Mackworth, A.K. (2010), Artificial intelligence: Foundations of computational agents, Cambridge University Press, Cambridge, USA.
49. Wilson, R.A. and Keil, F.C. eds (1999), The MIT encyclopedia of the cognitive sciences, The MIT Press, Massachsetts, USA.
50. Siebers, P.-O. and Aickelin, U. (2008), Introduction to multi-agent simulation, Encyclopedia of decision making and decision support technologies, Ed. by Adam, F., Humphreys, P., IGI Global.
51. Brenner, W., Zarnekow, R. and Schubert, C. (1998), Intelligent software agents: foundations and applications, Springer-Verlag.
52. Green, S., Hurst, L., Nangle, B., Cunningham, P., Somers, F. and Evans, R. (1997), Software agents: A review. Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-1997-06.
53. Janca, P.С. and Gilbert, D. (1998), Practical design of intelligent agent systems. Agent technology:Foundations, applications, and markets, Edited by Jennings, N.R. and Wooldridge, M.J., Springer, pp. 73-89.
54. Genesereth, M.R. and Ketchpel, S.P. (1994), Software agents, Communications of ACM, Vol. 37, no. 7, pp. 48-53.
55. Subrahmanian, V.S. et al. (2000), Heterogeneous agent systems, The MIT Press, Massachusetts, USA.
56. Zhang, Z. and Zhang, C. (2004), Agent-based hybrid intelligent systems: An agent-based framework for complex problem solving, Springer.
57. Bordini, R.H. et al. eds. (2005), Multi-agent programming: Languages, platforms and applications, Springer.
58. Yampolskiy, R.V. (2016), Artificial superintelligence: A futuristic approach, CRC Press.
59. Hibbard, B. (2012), Model-based utility functions, Journal of Artificial General Intelligence, Vol. 3, Iss. 1, pp. 1-24.
60. Orseau, L. and Ring, M. (2011), Self-modification and mortality in artificial agents, Proceedings of the 4th International Conference on Artificial General Intelligence (AGI 2011), USA, pp. 1-10.
61. Brazier, F.M., Wijngaards, N.J.E. (2001), Designing Self-Modifying Agents, Proceedings of International Conference of Computational and Cognitive Models of Creative Design V, Sydney, pp. 93-112.
62. Lin, L.-J. (1992), Self-reactive agents based on reinforcement learning, planning and teaching, Machine Learning, Vol. 8, pp. 293-321.
63. Schmidhuber, J. (1999), A general method for incremental self-improvement and multiagent learning in unrestricted environments, Evolutionary Computation: Theory and Applications, World Scientific Publishing Co, pp. 81-123.
64. Yampolskiy, R.V., Ashby, L. and Hassan, L. (2012), Wisdom of artificial crowds – a metaheuristic algorithm for optimization, Journal of Intelligent Learning Systems and Applications, Vol. 4, pp. 98-107.
65. Zimmermann, J., Henze, H.H. and Cremers, A.B. (2015), G`del agents in a scalable synchronous agent framework, Proceedings of the 8th International Conference on Artificial General Intelligence (AGI 2015), Germany, pp. 404-413.
66. Wang, S. (2016), Towards dynamic epistemic learning of actions for self-improving agents and multi-agent systems, Proceedings of IEEE International Conference on Autonomic Computing (ICAC 2016), Germany, pp. 292-299.
67. Mahoney, M. A model for recursively self improving programs, available at: http://mattmahoney.net/rsi.pdf.
68. Steunebrink, B.R., Thórisson, K.R. and Schmidhuber, J. (2016), Growing recursive selfimprovers, Proceedings of the 9th International Conference on Artificial General Intelligence
(AGI 2016), USA, pp. 129-139.
69. Yampolskiy, R.V. (2015), On the limits of recursively self-improving AGI, Proceedings of the 8th International Conference on Artificial General Intelligence (AGI 2015), Germany, pp. 394-403.
70. Ginodman, V.A., Obelets, N.V. and Pavlov, A.A. (2014), Ot pervykh virusov do tselevykh atak [From first viruses to target attacks], NIYaU MIFI, Moscow, Russia.
71. Kaspersky, K. (2005), Zapiski issledovatelya kompyuternykh virusov [The notes of the computer virus surveyor], Piter, St.Petersburg, Russia.
72. Klimentyev, K.E. (2013), Kompyuternyie virusy i antivirusy:vzglyad programmista [Computer viruses and anti-viruses: the programmer’s view], DMK Press, Moscow, Russia.
73. Gordon, Ya. (2004), Kompyuternyie virusy bez sekretov [Computer viruses without secrets], Novyi izdatelskii dom, Moscow, Russia.
74. Bonfante, G., Marion, J.-Y. and Reynaud-Plantey, D. (2009), A computability perspective on self-modifying programs, Proceedings of the Seventh IEEE International Conference on Software Engineering and Formal Methods, USA, pp. 231-239.
75. Rennard, J.-P. ed. (2007), Handbook of research on nature inspired computing for economics and management, Idea Group Inc.
76. Alkhateeb, F., Maghayreh, E.A. and Doush, I.A. (2011), Multi-agent systems – modeling, control, programming, simulations and applications, InTech.
77. Barnes, D.J. and Chu, D. (2010), Introduction to modeling for biosciences, Springer.
78. Meyer, R. (2015), Event-driven multi-agent simulation, Proceedings of International Workshop “Multi-Agent-Based Simulation” (MABS 2014), Springer, Paris, France, pp. 3-16.
79. Uhrmacher, A.M. and Weyns, D. (2009), Multi-agent systems: simulation and applications, CRC Press.
80. Reynolds, C. (1987), Flocks, herds and schools: A distributed behavioral model, Proceedings of the 14th annual conference on Computer graphics and interactive techniques (SIGGRAPH’87), pp. 25-34.
81. Aitken, M., Butler, G., Lemmon, D., Saindon, E., Peters, D. and Williams, G. (2004), The lord of the rings: the visual effects that brought middle earth to the screen, International Conference on Computer Graphics and Interactive Techniques (SIGGRAPH’04), Course Notes, Article № 11, Los Angeles, USA.
82. Burke, R., Isla, D., Downie, M., Ivanov, Y. and Blumberg, B. (2002), Creature smarts: The art and architecture of a virtual brain, Proceedings of the 3rd International Conference on Intelligent Games and Simulation (Game-On 2002), Westminster, UK, pp. 89-93.
83. Perlin, K. and Goldberg, A. (1996), Improv: A system for scripting interactive actors in virtual worlds, Proceedings of the ACM Computer Graphics Annual Conference, NY, USA, pp. 205-216.
84. Musse, S.R. and Thalmann, D. (2001), Hierarchical model for real time simulation of virtual human crowds, IEEE Transactions on Visualization and Computer Graphics, Vol. 7, no. 2, pp. 152-164.
85. Buckland, M. (2005), Programming game AI by example, Wordware Publishing, Inc.
86. Gemrot, J., Kadlec, R., BRda, M., Burkert, O., et al. (2009), Pogamut 3 can assist developers in building AI (not only) for their videogame agents, Agents for games and simulations. Trends in techniques, concepts and design, Edited by Dignum, F., Bradshaw, J., Silverman, B., van Doesburg, W. Springer, pp. 1-15.
87. Bedau, M.A. (2007), Artificial life. Handbook of the Philosophy of Biology, Edited by Matthen, M., Stephens, C., Elsevier.
88. Kumar, A. (2012), An overview of abstract and physical characteristics “Artificial Life Systems”, International Journal of Scientific and Research Publications, Vol. 2, Iss. 12, pp. 1-7.
89. Banzhaf, W. and McMullin, B. (2012), Artificial life. Handbook of Natural Computing, Edited
by Rozenberg, D., Springer.
90. Komosinski, M. and Adamatzky, A. eds. (2009), Artificial life models in software, Springer.

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