Volume 5, Issue 1, January 2017, Page: 8-25
A Concise Overview of Software Agent Research, Modeling, and Development
Salama A. Mostafa, College of Graduate Studies, Universiti Tenaga Nasional, Selangor, Malaysia
Mohd Sharifuddin Ahmad, College of Information Technology, Universiti Tenaga Nasional, Selangor, Malaysia
Aida Mustapha, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn, Johor, Malaysia
Mazin Abed Mohammed, Faculty of Communication and Information Engineering, University Technical Malaysia, Melaka, Malaysia
Received: Jan. 6, 2017;       Accepted: Jan. 24, 2017;       Published: Mar. 4, 2017
DOI: 10.11648/j.se.20170501.12      View  1831      Downloads  97
Abstract
Software agent technology has been intensively explored in the past three decades. It is explicitly or implicitly applied in many systems. Software agent research covers a wide range of area which makes it challenging for new researchers to comprehend the peculiarities and complexities of the technology. Consequently, this paper provides a concise overview of software agent research, modeling, and development. It summarizes and analyzes more than 100 sources of publication including research papers, articles, and books. The aim of the paper is to provide a quick start to new researchers in software agent and multi-agent systems. The paper offers the following contributions: (1) it determines the milestone achievements of software agent conceptualization, modeling and development platforms, (2) it defines the related terminologies of the field and reveals their redundancies, (3) it summarizes the multi-agent systems technology and finally, (4) it explores the current active research topics in software agent and multi-agent systems.
Keywords
Software Agent, Multi-agent System, Agent-Oriented Programming, Agent Models
To cite this article
Salama A. Mostafa, Mohd Sharifuddin Ahmad, Aida Mustapha, Mazin Abed Mohammed, A Concise Overview of Software Agent Research, Modeling, and Development, Software Engineering. Vol. 5, No. 1, 2017, pp. 8-25. doi: 10.11648/j.se.20170501.12
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Mostafa, S. A., Ahmad, M. S., Annamalai, M., Ahmad, A., & Gunasekaran, S. S. (2013). A dynamically adjustable autonomic agent framework. Advances in Intelligent Systems and Computing, Springer Verlag, 206, 631-642.
[2]
Mohammed, K. A., Mostafa, S. A., Ahmad, M. S., & Mahmoud, M. A. (2014, November). A qualitative analysis of human-agent functions for collaborative multi-agent system. In Information Technology and Multimedia (ICIMU), 2014 International Conference on (pp. 244-249). IEEE.
[3]
Pătraşcu, M., & Drăgoicea, M. (2014). Integrating agents and services for control and monitoring: managing emergencies in smart buildings. In Service Orientation in Holonic and Multi-Agent Manufacturing and Robotics (pp. 209-224). Springer International Publishing.
[4]
Byrski, A., Dreżewski, R., Siwik, L., & Kisiel-Dorohinicki, M. (2015). Evolutionary multi-agent systems. The Knowledge Engineering Review, 30 (02), 171-186.
[5]
Maes, P. (1993). Modeling adaptive autonomous agents. Artificial life, 1 (1-2), 135-162.
[6]
Maes, P. (1995). Artificial life meets entertainment: Lifelike autonomous agents. Communications of the ACM, 38 (11), 108-114.
[7]
Jennings, N. R., Sycara, K., & Wooldridge, M. (1998). A roadmap of agent research and development. Autonomous agents and multi-agent systems, 1 (1), 7-38.
[8]
Magill, K., & Erden, Y. J. (2012). Autonomy and desire in machines and cognitive agent systems. Cognitive Computation, 4 (3), 354-364.
[9]
Chira, C. (2003). Software agents. IDIMS Report, 21.
[10]
McBurney, P., & Luck, M. (2007). The agents are all busy doing stuff!. IEEE Intelligent Systems, (4), 6-7.
[11]
Wooldridge, M. (2009). An introduction to multi-agent systems. John Wiley & Sons.
[12]
Ehlert, P. (2001). Intelligent driving agents: The agent approach to tactical driving in autonomous vehicles and traffic simulation.
[13]
Hewitt, C. (1977). Viewing control structures as patterns of passing messages. Artificial intelligence, 8 (3), 323-364.
[14]
Florian, R. V. (2003). Autonomous artificial intelligent agents. Center for Cognitive and Neural Studies (Coneural), Str. Saturn, 24, 3400.
[15]
Wooldridge, M., & Jennings, N. R. (1995). Intelligent agents: Theory and practice. The knowledge engineering review, 10 (02), 115-152.
[16]
Nwana, H. S., & Ndumu, D. T. (1997). An introduction to agent technology. In Software Agents and Soft Computing Towards Enhancing Machine Intelligence (pp. 1-26). Springer Berlin Heidelberg.
[17]
Franklin, S., & Graesser, A. (1997). Is it an agent, or just a program?: A Taxonomy for Autonomous Agents. In Intelligent agents III agent theories, architectures, and languages (pp. 21-35). Springer Berlin Heidelberg.
[18]
Shoham, Y. (1997). An overview of agent-oriented programming. In Software agents. Bradshaw, J. M editor, AAAI Press / The MIT Press, Cambridge, Massachusetts.
[19]
Bradshaw, J. M. (1997). Software agents. MIT press.
[20]
Hexmoor, H., Castelfranchi, C., & Falcone, R. (2003). A prospectus on agent autonomy. In Agent Autonomy (pp. 1-10). Springer US.
[21]
Bhatia, R. (2014). Intelligent agents: A Deep insight. IJCAIT, 4 (2), 11-13.
[22]
Nwana, H. S. (1996). Software agents: An overview. The knowledge engineering review, 11 (03), 205-244.
[23]
Nwana, H. S., & Wooldridge, M. (1996). Software agent technologies. BT Technology Journal, 14 (4).
[24]
Franklin, S., & Graesser, A. (1997). Is it an agent, or just a program?: A Taxonomy for Autonomous Agents. In Intelligent agents III agent theories, architectures, and languages (pp. 21-35). Springer Berlin Heidelberg.
[25]
Mohammed, K. A., Ahmad, M. S., Mostafa, S. A., & Firdaus, M. A. (2012). A Nodal Approach to Modeling Human-Agents Collaboration. International Journal of Computer Applications, 43 (12), 33-40.
[26]
Bellifemine, F. L., Caire, G., & Greenwood, D. (2007). Developing multi-agent systems with JADE (Vol. 7). John Wiley & Sons.
[27]
Georgeff, M., Pell, B., Pollack, M., Tambe, M., & Wooldridge, M. (1999). The belief-desire-intention model of agency. In Intelligent Agents V: Agents Theories, Architectures, and Languages (pp. 1-10). Springer Berlin Heidelberg.
[28]
Durand, B., Godary-Dejean, K., Lapierre, L., & Crestani, D. (2009). Inconsistencies evaluation mechanisms for a hybrid control architecture with adaptive autonomy. In CAR'09: 4th National Conference on Control Architectures of Robots.
[29]
Brooks, R. (1986). A robust layered control system for a mobile robot. Robotics and Automation, IEEE Journal of, 2 (1), 14-23.
[30]
Brooks, R. A. (1991). Intelligence without representation. Artificial intelligence, 47 (1), 139-159.
[31]
Schumann, R. (2011). Engineering coordination: a methodology for the coordination of planning systems.
[32]
Nau, D. S. (2007). Current trends in automated planning. AI magazine, 28 (4), 43.
[33]
Molineaux, M., Klenk, M., & Aha, D. W. (2010). Goal-driven autonomy in a Navy strategy simulation. KNEXUS Research Corp Springfield VA.
[34]
Ceballos, A., Bensalem, S., Cesta, A., De Silva, L., Fratini, S., Ingrand, F., Ocon, J., Orlandini, A., Py, F., Rajan, K., &Rasconi, R. (2011). A goal-oriented autonomous controller for space exploration. ASTRA, 11.
[35]
Wilson, M. A., McMahon, J., & Aha, D. W. (2014). Bounded expectations for discrepancy detection in goal-driven autonomy. In Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence.
[36]
Muñoz-Avila, H., Aha, D. W., Jaidee, U., Klenk, M., & Molineaux, M. (2010). Applying goal driven autonomy to a team shooter game. In FLAIRS Conference.
[37]
Georgeff, M. P., & Lansky, A. L. (1987). Reactive reasoning and planning. In AAAI (Vol. 87, pp. 677-682).
[38]
Rao, A. S., & Georgeff, M. P. (1995). BDI agents: From theory to practice. In ICMAS (Vol. 95, pp. 312-319).
[39]
Bratman, M. (1987). Intention, plans, and practical reason.
[40]
Hoogendoorn, M., Van Lambalgen, R. M., & Treur, J. (2011). Modeling situation awareness in human-like agents using mental models. In IJCAI Proceedings-International Joint Conference on Artificial Intelligence (Vol. 22, No. 1, p. 1697).
[41]
Schut, M., Wooldridge, M., & Parsons, S. (2004). The theory and practice of intention reconsideration. Journal of Experimental & Theoretical Artificial Intelligence, 16 (4), 261-293.
[42]
Pantelis, P. C., Baker, C. L., Cholewiak, S. A., Sanik, K., Weinstein, A., Wu, C. C., Tenenbaum, J. B., & Feldman, J. (2014). Inferring the intentional states of autonomous virtual agents. Cognition, 130 (3), 360-379.
[43]
Mostafa, S. A., Ahmad, M. S., Ahmad, A., Annamalai, M., & Mustapha, A. (2014). A dynamic measurement of agent autonomy in the layered adjustable autonomy model. Studies in Computational Intelligence, Springer-Verlag, 513, 513, 25-35.
[44]
Mostafa, S. A., Ahmad, M. S., Tang, A. Y., Ahmad, A., Annamalai, M., & Mustapha, A. (2014). Agent’s autonomy adjustment via situation awareness. Lecture Notes in Computer Science, Springer-Verlag, 8397, 443-453.
[45]
Ferguson, I. A. (1991). Toward an architecture for adaptive, rational, mobile agents. ACM SIGOIS Bulletin, 13 (3), 15.
[46]
Müller, J. P. (1996). The design of intelligent agents: a layered approach (Vol. 1177). Springer Science & Business Media.
[47]
Kong, L., & Xiao, L. (2007). A multi-layered control architecture of intelligent agent. In Control and Automation, 2007. ICCA 2007. IEEE International Conference on (pp. 1454-1458). IEEE.
[48]
Wallace, S. A., & Henry, M. (2008). Towards a generic infrastructure to adjust the autonomy of Soar agents. In FLAIRS Conference (pp. 119-120).
[49]
Barber, K. S. (1996). The architecture for sensible agents. In Proceedings of the International Multidisciplinary Conference, Intelligent Systems: A Semiotic Perspective (pp. 49-54).
[50]
Torreño, A., Onaindia, E., & Sapena, Ó. (2015). An approach to multi-agent planning with incomplete information. arXiv preprint arXiv:1501.07256.
[51]
Andreadis, G., Bouzakis, K. D., Klazoglou, P., & Niwtaki, K. (2014). Review of Agent-Based Systems in the Manufacturing Section. Universal Journal of Mechanical Engineering, 2 (2), 55-59.
[52]
Parunak, H. V. D. (1997). " Go to the ant": Engineering principles from natural multi-agent systems. Annals of Operations Research, 75, 69-101.
[53]
Odell, J. (2002). Objects and agents compared. Journal of object technology, 1 (1), 41-53.
[54]
Fisher, M. (1994). A survey of Concurrent METATEM—the language and its applications. In Temporal Logic (pp. 480-505). Springer Berlin Heidelberg.
[55]
Bradshaw, J. M., Dutfield, S., Benoit, P., & Woolley, J. D. (1997). KAoS: Toward an industrial-strength open agent architecture. Software agents, 375-418.
[56]
Howden, N., Rönnquist, R., Hodgson, A., & Lucas, A. (2001). JACK intelligent agents-summary of an agent infrastructure. In 5th International conference on autonomous agents.
[57]
Sycara, K., Paolucci, M., Van Velsen, M., & Giampapa, J. (2003). The retsina MAS infrastructure. Autonomous agents and multi-agent systems, 7 (1-2), 29-48.
[58]
Grigoryev I. " AnyLogic 7 in Three Days: A Quick Course in Simulation Modeling ". [Hampton, NJ]: Kindle Edition, 2014. http://www.anylogic.com/books
[59]
Kinny, D., & George, M. (1991). Commitment and effectiveness of situated agents. In IJCAI-91 (pp. 82-88).
[60]
Ermon, S., Gomes, C., Selman, B., & Vladimirsky, A. (2012). Probabilistic planning with non-linear utility functions and worst-case guarantees. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, Vol 2 (pp. 965-972). International Foundation for Autonomous Agents and Multi-agent Systems.
[61]
Pokahr, A., Braubach, L., & Lamersdorf, W. (2005). A goal deliberation strategy for BDI agent systems. In Multiagent System Technologies (pp. 82-93). Springer Berlin Heidelberg.
[62]
Dastani, M., Dignum, F., & Meyer, J. J. (2004). Autonomy and agent deliberation. In Agents and Computational Autonomy (pp. 114-127). Springer Berlin Heidelberg.
[63]
Mostafa, S., Gunasekaran, S. S., Ahmad, M. S., Ahmad, A., Annamalai, M., & Mustapha, A. (2014). Defining tasks and actions complexity-levels via their deliberation intensity measures in the layered adjustable autonomy model. In Intelligent Environments (IE), 2014 International Conference on (pp. 52-55). IEEE.
[64]
Larson, K., & Sandholm, T. (2005). Mechanism design and deliberative agents. In Proceedings of the fourth international joint conference on Autonomous agents and multi-agent systems (pp. 650-656). ACM.
[65]
Black, L. W., Burkhalter, S., Gastil, J., & Stromer-Galley, J. (2011). Methods for analyzing and measuring group deliberation. Sourcebook of political communication research: Methods, measures, and analytical techniques, 323-345.
[66]
Lizzeri, A., & Yariv, L. (2010). Sequential deliberation. Available at SSRN 1702940.
[67]
Fleming, M., & Cohen, R. (2004). A decision procedure for autonomous agents to reason about interaction with humans. In Proceedings of the AAAI 2004 Spring Symposium on Interaction between Humans and Autonomous Systems over Extended Operation (pp. 81-86).
[68]
Mostafa, S., Ahmad, M. S., Ahmad, A., & Annamalai, M. (2013). Formulating situation awareness for multi-agent systems. In Advanced Computer Science Applications and Technologies (ACSAT), (pp. 48-53). IEEE.
[69]
Mostafa, S. A., Ahmad, M. S., Annamalai, M., Ahmad, A., & Gunasekaran, S. S. (2015). Formulating dynamic agents’ operational state via situation awareness assessment. Advances in Intelligent Systems and Computing, Springer Verlag, 320, 545-556.
[70]
Ferrando, S. P., & Onaindia, E. (2013). Context-aware multi-agent planning in intelligent environments. Information Sciences, 227, 22-42.
[71]
Wardziński, A. (2006). The role of situation awareness in assuring safety of autonomous vehicles. In Computer Safety, Reliability, and Security (pp. 205-218). Springer Berlin Heidelberg.
[72]
Mostafa, S. A., Ahmad, M. S., Ahmad, A., Annamalai, M., & Gunasekaran, S. S. (2015, August). An autonomy viability assessment matrix for agent-based autonomous systems. In Agents, Multi-Agent Systems and Robotics (ISAMSR), 2015 International Symposium on (pp. 53-58). IEEE.
[73]
McAree, O., & Chen, W. H. (2013). Artificial situation awareness for increased autonomy of unmanned aerial systems in the terminal area. Journal of Intelligent & Robotic Systems, 70 (1-4), 545-555.
[74]
Mostafa, S. A., Ahmad, M. S., Annamalai, M., Ahmad, A., & Gunasekaran, S. S. (2013). A conceptual model of layered adjustable autonomy. Advances in Intelligent Systems and Computing, Springer Verlag, 206, 619-630.
[75]
Jennings, N. R., Moreau, L., Nicholson, D., Ramchurn, S., Roberts, S., Rodden, T., & Rogers, A. (2014). Human-agent collectives. Communications of the ACM, 57 (12), 80-88.
[76]
Bradshaw, J. M., Feltovich, P. J., Jung, H., Kulkarni, S., Taysom, W., & Uszok, A. (2004). Dimensions of adjustable autonomy and mixed-initiative interaction. In Agents and Computational Autonomy (pp. 17-39). Springer Berlin Heidelberg.
[77]
Mostafa, S. A., Ahmad, M. S., Annamalai, M., Ahmad, A., & Basheer, G. S. (2013). A layered adjustable autonomy approach for dynamic autonomy distribution. Frontiers in Artificial Intelligence and Applications. IOS Publisher. 252, 335-345.
[78]
Alzahrani, A., Callaghan, V., & Gardner, M. (2013). Towards Adjustable Autonomy in Adaptive Course Sequencing. In Intelligent Environments (Workshops) (pp. 466-477).
[79]
Alan, A., Costanza, E., Fischer, J., Ramchurn, S. D., Rodden, T., & Jennings, N. R. (2014). A field study of human-agent interaction for electricity tariff switching. In Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems (pp. 965-972). International Foundation for Autonomous Agents and Multi-agent Systems.
[80]
Johnson, M., Bradshaw, J. M., Feltovich, P. J., Jonker, C. M., Van Riemsdijk, M. B., & Sierhuis, M. (2014). Coactive design: Designing support for interdependence in joint activity. Journal of Human-Robot Interaction, 3 (1), 2014.
[81]
Johnson, M., Bradshaw, J. M., Feltovich, P. J., Jonker, C., Van Riemsdijk, B., & Sierhuis, M. (2012). Autonomy and interdependence in human-agent-robot teams. Intelligent Systems, IEEE, 27 (2), 43-51.
[82]
Moffitt, V. Z., Franke, J. L., & Lomas, M. (2006). Mixed-initiative adjustable autonomy in multi-vehicle operations. Proceedings of AUVSI, Orlando, Florida.
[83]
Schurr, N., Marecki, J., & Tambe, M. (2008). RIAACT: A robust approach to adjustable autonomy for human-multi-agent teams. In Proceedings of the 7th international joint conference on Autonomous agents and multi-agent systems, Volume 3 (pp. 1429-1432). International Foundation for Autonomous Agents and Multi-agent Systems.
[84]
Gunasekaran, S. S., Mostafa, S. A., & Ahmad, M. S. (2015). Knowledge Transfer Model in Collective Intelligence Theory. In Advances in Intelligent Informatics (pp. 481-491). Springer International Publishing.
[85]
Salminen, J. (2012). Collective intelligence in humans: A literature review.arXiv preprint arXiv:1204.3401.
[86]
Gunasekaran, S. S., Mostafa, S. A., Ahmad, M. S., & Tang, A. Y. (2015, August). Identifying variables dependency that influences a high level deliberation process in a CI-based Multi-agent System. In Agents, Multi-Agent Systems and Robotics (ISAMSR), 2015 International Symposium on (pp. 24-29). IEEE.
[87]
Brambilla, M., Ferrante, E., Birattari, M., & Dorigo, M. (2013). Swarm robotics: a review from the swarm engineering perspective. Swarm Intelligence, 7 (1), 1-41.
[88]
Gunasekaran, S. S., Mostafa, S. A., & Ahmad, M. S. (2013, December). Personal and extended intelligence in collective emergence. In Intelligent Systems Design and Applications (ISDA), 2013 13th International Conference on (pp. 199-204). IEEE.
[89]
Gunasekaran, S. S., Mostafa, S. A., & Ahmad, M. S. (2014, November). Using the Internet as a Collective Intelligence platform in harnessing issues on Climate Change. In Information Technology and Multimedia (ICIMU), 2014 International Conference on (pp. 130-135). IEEE.
[90]
Ahmad, A., Ahmed, M., M. Yusoff, M. Z, Ahmad, M. S, & Mustapha, A. (2011). Resolving Conflicts between Personal and Normative Goals in Normative Agent Systems, The Seventh International Conference on IT in Asia 2011 (CITA 2011), pp. 153 – 158, Kuching, Sarawak, 12 – 14 July 2011.
[91]
Mahmoud, M. A., Ahmad, M. S., Mohd Yusoff, M. Z., & Mustapha, A. (2014). A review of norms and normative multiagent systems. The Scientific World Journal, 2014.
[92]
Savarimuthu B. T. R., S. Cranefield, M. Purvis, M. Purvis, (2010). Obligation Norm Identification in Agent Societies. Journal of Artificial Societies and Social Simulation, 13 (4).
[93]
Alberti, M., Gomes, A. S., Goncalves, R., Leite, J., & Slota, M., (2011). Normative Systems Represented as Hybrid Knowledge Bases, Proceedings of the 12th International Conference on Computational Logic in Multi-agent Systems, CLIMA'11, Lecture Notes in Computer Science, pp 330-346.
[94]
C. D. Hollander and A. S. Wu, “The Current State of Normative AgentBased Systems,” Journal of Artificial Societies and Social Simulation, 14 (2), pp. 6, 2011.
[95]
Hamid, A., Hamimah, N., Ahmad, M. S., Ahmad, A., Mahmoud, M. A., Mohd Yusoff, M. Z., & Mustapha, A. (2014, November). Trusting norms in normative multi-agent systems. In Information Technology and Multimedia (ICIMU), 2014 International Conference on (pp. 217-222). IEEE.
[96]
Hsu, C. M., Chen, T. T., & Heh, J. S. (2014, July). Emotional and Conditional Model for Pet Robot based on Neural Network. In Ubi-Media Computing and Workshops (UMEDIA), 2014 7th International Conference on (pp. 305-308). IEEE.
[97]
Subramainan, L., Yusoff, M. Z. M., & Mahmoud, M. A. (2015, August). A classification of emotions study in software agent and robotics applications research. In Agents, Multi-Agent Systems and Robotics (ISAMSR), 2015 International Symposium on (pp. 41-46). IEEE.
[98]
Harley, J. M., Bouchet, F., Hussain, M. S., Azevedo, R., & Calvo, R. (2015). A multi-componential analysis of emotions during complex learning with an intelligent multi-agent system. Computers in Human Behavior, 48, 615-625.
[99]
Nair, R., Tambe, M., & Marsella, S. (2005). The role of emotions in multiagent teamwork. Who Needs Emotions, 311-329.
[100]
Ngo, T. D., & Bui, T. D. (2015, January). A Vietnamese 3D taking face for embodied conversational agents. In Computing & Communication Technologies-Research, Innovation, and Vision for the Future (RIVF), 2015 IEEE RIVF International Conference on (pp. 94-99). IEEE.
[101]
Velez, R. A. (2015). Sincere and sophisticated players in an equal-income market. Journal of Economic Theory, 157, 1114-1129.
[102]
Velez, R. A. (2013, January). Sincere and sophisticated players in the envy-free allocation problem. In EC (pp. 853-854).
[103]
Sullins, J. P. (2006). When is a robot a moral agent?
[104]
Floridi, L., & Sanders, J. W. (2011). On the morality of artificial agents. Machine ethics, 151-160.
[105]
Floridi, L. (2013). Distributed morality in an information society. Science and engineering ethics, 19 (3), 727-743.
[106]
Ahmad, A., Ahmed, M., Yusof, M. Z. M., Ahmad, M. S., & Mustapha, A. (2016). Resolving Conflicts between Personal and Normative Goals in Normative Agent Systems. Journal of IT in Asia, 4 (1), 1-12.
[107]
Jaafar, N. H., Ahmad, M. S., & Ahmad, A. (2015). Operational rules for implementing sincere software agents in corrective and preventive actions environment. In Computational Intelligence in Information Systems (pp. 307-314). Springer International Publishing.
Browse journals by subject