A Computational Data Model of Intelligent Agents with Time-Varying Resources
This paper aims to develop a generic and complete computation model toward scheduling, resource allocation, and action model of agents and to design the relevant simulated intelligent agent framework for agent applications. We propose a computation model and development tools to deal with dynamic data, translation of data models, qualitative information, time quantity, uncertainty, functionality, and semantic analysis. We also develop the relevant grammar and algebra system to locate resources and maintain constrains. The system allow user to define percepts and actions of agents. Script language with percept lists are integrated with scheduling and resource allocations. Several computation algorithms and operation tables which include a set of complete temporal logics are proposed. The combined temporal data models are generalized by composing point and interval algebra with qualitative and quantitative functions. The table look-up mechanism has the advantages for computation and realization.
KeywordsIntelligent agents Scheduling Resource allocation Wireless sensor networks Semantic analysis
This work is supported by the National Science Council of Taiwan, under Grant NSC-101-2221-E-240-003.
- 1.Ferber J (1999) Multi-agent systems: an introduction to distributed artificial intelligence. Addison Wesley Longman Inc, New YorkGoogle Scholar
- 2.Biniaris CG, Antonis IK, Dimitra IK, Iakovos SV (2002) Implementing distributed FDTD codes with java mobile agents. IEEE Antennas Propag Mag 44(6):115–119.Google Scholar
- 3.Hur Y, Lee I (2002) Distributed simulation of multi-agent hybrid systems. In: Proceedings of fifth IEEE international symposium on object-oriented real-time distributed computing, (ISORC 2002), 29 April–1 May, Washington, pp 356–364Google Scholar
- 4.Mishra S, Xie P (2001) Interagent communication and synchronization in DaAgent. In: Proceedings of 21st international conference on distributed computing systems, 16–19 April 2001, Mesa, pp 699–702Google Scholar
- 5.Rai A, Bhagwan R, Guha S (2012) Generalized Resource Allocation for the Cloud. In: Proceedings of the third ACM symposium on cloud computing, SoCC ‘12, Oct 2012Google Scholar
- 6.Lama P, Zhou X (2012) AROMA: automated resource allocation and configuration of MapReduce environment in the cloud. In: Proceedings of the 9th international conference on Autonomic computing, ICAC’12, Sept 2012, pp 63–72Google Scholar
- 8.Calinescu G, Chakrabarti A, Karloff H, Rabani Y (2011) An improved approximation algorithm for resource allocation. Trans Algor (TALG) 7(4) Article 48Google Scholar
- 9.Shih TK, Chang AY (1998) The algebra of spatio-temporal intervals. In: Proceedings of the 12th international conference on information networking, Jan 21–23, 1998Google Scholar
- 10.Allen JF (1983) Maintaining knowledge about temporal intervals. Commun ACM 26(11) Google Scholar