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Embedding intelligent decision making within complex dynamic environments

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Abstract

Decision-making is a complex and demanding process often constrained in a number of possibly conflicting dimensions including quality, responsiveness and cost. This paper considers in situ decision making whereby decisions are effected based upon inferences made from both locally sensed data and data aggregated from a sensor network. Such sensing devices that comprise a sensor network are often computationally challenged and present an additional constraint upon the reasoning process. This paper describes a hybrid reasoning approach to deliver in situ decision making which combines stream based computing with multi-agent system techniques. This approach is illustrated and exercised through an environmental demonstrator project entitled SmartBay which seeks to deliver in situ real time environmental monitoring.

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References

  • Amini L, Jain N, Sehgal A, Silber J, Verscheure O (2006) Adaptive control of extreme-scale stream processing systems. In: ICDCS ’06: Proceedings of the 26th IEEE international conference on distributed computing systems, IEEE Computer Society, Washington, DC, USA, p 71

  • Berger M, Rusitschka S, Toropov D, Watzke M, Schlichte M (2003) The development of the lightweight extensible agent platform. TILAB Journal—Special Issue on JADE 3(3): 32–41

    Google Scholar 

  • Branson M, Douglis F, Fawcett B, Liu Z, Riabov A, Ye F (2007) Clasp: olaborating, utonomous tream rocessing systems. In: Cerqueira R, Campbell RH (eds) Middleware, Springer, Lecture Notes in Computer Science, vol 4834:348–367

  • Chan C, Huang G (2003) Artificial intelligence for management and control of pollution minimization and mitigation processes. Eng Appl Artif Intell 16(16): 75–90

    Article  Google Scholar 

  • Chen Q, Mynett AE (2006) Modelling algal blooms in the dutch coastal waters by integrated numerical and fuzzy cellular automata approaches. Ecol Model 199: 73–81

    Article  Google Scholar 

  • Chen J, O’Grady MJ, O’Hare GMP (2006) Autonomy and intelligence—opportunistic service delivery in mobile computing, Lecture Notes in Artificial Intelligence (LNAI), vol 4253, Springer-Verlag, pp 1201–1207

  • Feng Y, Long T, Liu R, Guo J, Liu X (2003) Study on biological filter anaerobic wastewater treatment hybrid intelligent control. Proceedings of the 4th international conference on control and automation (ICCA’03) pp 441–445

  • Fleming G, van der Merwe M, McFerren G (2007) Fuzzy expert systems and gis for cholera health risk prediction in southern africa. Environ Model Softw 22(4): 442–448

    Article  Google Scholar 

  • Fok CL, Roman GC, Lu C (2005) Mobile agent middleware for sensor networks: an application case study. In: Proc. of the 4th Int. Conf. on Information Processing in Sensor Networks (IPSN’05), IEEE, pp 382–387

  • Fregene K, Kennedy D, Madhavan R, Parker LE, Wang D (2005) A class of intelligent agents for coordinated control of outdoor terrain mapping UGVs. Eng Appl Artif Intell 5

  • Gedik B, Andrade H, Wu KL, Yu PS, Doo M (2008) Spade: the system s declarative stream processing engine. In: SIGMOD ’08: Proceedings of the 2008 ACM SIGMOD international conference on management of data, ACM, New York, NY, USA, pp 1123–1134

  • Heaton JT (2005) Introduction to neural networks with Java. Heaton Research Inc.

  • IBM (2008) Unstructured information management architecture (UIMA). http://www.research.ibm.com/UIMA/

  • Jain N, Amini L, Andrade H, King R, Park Y, Selo P, Venkatramani C (2006) Design, implementation, and evaluation of the linear road bnchmark on the stream processing core. In: SIGMOD ’06: Proceedings of the 2006 ACM SIGMOD international conference on management of data, ACM, New York, NY, USA, pp 431–442

  • Keegan S, O’Hare GMP, O’Grady MJ (2008) Easishop: ambient intelligence assists everyday shopping. Inf Sci 178(3): 588–611

    Article  Google Scholar 

  • Khalique S, Farooq S, Ahmad HF, Suguri H, Ali A (2007) Sage-lite: an architecture and implementation of light weight multiagent system. ISADS 0:239–244, http://doi.ieeecomputersociety.org/10.1109/ISADS.2007.68

  • Koch F, Meyer JJ, Dignum F, Rahwan I (2005) Programming deliberative agents for mobile services: the 3APL-M platform. AAMAS’05 Workshop on Programming Multi-Agent Systems (ProMAS05) pp 222–235

  • Muldoon C (2007) An agent framework for ubiquitous services. PhD thesis, School of Computer Science and Informatics, Dublin, Ireland

  • Muldoon C, O’Hare GMP, Phelan D, Strahan R, Collier RW (2003) ACCESS: an Agent architecture for ubiquitous service delivery. In: Proceedings 7th international workshop on Cooperative Information Agents (CIA), Springer, Helsinki, Lecture Notes in Computer Science, vol 2782, pp 1–15

  • Muldoon C, O’Hare GMP, Collier RW, O’Grady MJ (2006) Agent factory micro edition: a framework for ambient applications. In: Intelligent agents in computing systems, Springer, Reading, UK, Lecture Notes in Computer Science, vol 3993, pp 727–734

  • O’Grady MJ, O’Hare GMP (2004) Gulliver’s genie: agency mobility adaptivity. Comput Graph 28(5): 677–689

    Article  Google Scholar 

  • O’Grady MJ, O’Hare GMP (2005) Mobile devices and intelligent agents: towards a new generation of applications and services. Inf Sci 171(4): 335–353

    Article  Google Scholar 

  • O’Hare GMP, O’Grady MJ, Muldoon C, Bradley JF (2006) Embedded agents: a paradigm for mobile services. Int J Web Grid Serv 2(4): 379–405

    Article  Google Scholar 

  • Rao AS, Georgeff MP (1995) BDI Agents: from theory to practice. Proceedings of the first international conference on multi-agent systems (ICMAS’95) pp 312–319

  • Recknagel F, Petzoldt T, Jaeke O, Krusche F (1994) Hybrid expert system delaqua—a toolkit for water quality control of lakes and reservoirs. Ecol Model 71(1-3): 17–36

    Article  Google Scholar 

  • Shen S, O’Hare GMP (2008) Fuzzy decision making through energy-aware and utility agents within wireless sensor networks. Artificial Intelligence Review

  • Taha I, Ghosh J (1995) A hybrid intelligent architecture and its application to water reservoir control. Int J Smart Eng Syst 1: 59–75

    Google Scholar 

  • Wright W, Moore D (2003) Design considerations for multiagent systems on very small platforms. In: AAMAS ’03: Proceedings of the second international joint conference on autonomous agents and multiagent systems, ACM Press, New York, NY, USA, pp 1160–1161

  • Wu F (1998) Simulating urban encroachment on rural land with fuzzy-logic-controlled cellular automata in a geographical information system. J Environ Manag 53(4): 293–308

    Article  Google Scholar 

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Correspondence to G. M. P. O’Hare.

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O’Hare, G.M.P., O’Grady, M.J., Tynan, R. et al. Embedding intelligent decision making within complex dynamic environments. Artif Intell Rev 27, 189–201 (2007). https://doi.org/10.1007/s10462-008-9089-y

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