Mathematical model for dynamic case-based planning

International Journal of Computer Mathematics

Volumn 86, Issue 10-11, 2009, Pages 1719-1730

  De Paz, J F ^a   Rodriguez S ^a   Bajo, J ^a   Corchado, J M ^a  

^a UNIVERSITY OF SALAMANCA   (Spain)

Author keywords

Ambient inteligent; Beliefs; Case based reasoning; Cased based planning; Desires; Intentions; Multi agent systems; RFID; Self organized maps

Indexed keywords

AMBIENT INTELIGENT; BELIEFS; DESIRES; INTENTIONS; SELF-ORGANIZED MAPS;

MATHEMATICAL MODELS; MULTI AGENT SYSTEMS; NEURAL NETWORKS; RADIO FREQUENCY IDENTIFICATION (RFID);

CONTEXT SENSITIVE GRAMMARS;

EID: 76249103837     PISSN: 00207160     EISSN: 10290265     Source Type: Journal    
DOI: 10.1080/00207160802562556     Document Type: Conference Paper

References (17)

1. J. Allen, Towards a general theory of action and time, Artif. Intell. 23 (1984), pp. 123-154.
2. D. Apostolou, G. Mentzas, B. Klein, A. Abecker, and W. Maass, Interorganizational knowledge exchanges, IEEE Intell. Syst. 23 (2008), pp. 65-74.
3. J. Bajo, V. Julián, J.M. Corchado, C. Carrascosa,Y. Pazade, V. Bottib, and J.F. Pazde, An execution time planner for the artis agent architecture, IEEE Intell. Syst. 21 (2008), pp. 769-784.
4. P. Chang and C. Lai, A hybrid system combining self-organizing maps with case-based reasoning in wholesaler's new-release book forecasting, Expert Syst. Appl. 29 (2005), pp. 183-192.
5. J. Corchado, J. Bajo, and A. Abraham, Gerami: improving the delivery of health care (special issue on ambient intelligence), IEEE Intell. Syst. 3 (2008), pp. 19-25.
6. J. Corchado and R. Laza, Constructing deliberative agents with case-based reasoning technology, Int. J. Intell. Syst. 18 (2003), pp. 1227-1241.
7. J. Créput andA.Koukama,A memetic neural network for the euclidean traveling salesman problem, Neurocomputing 72 (2009), pp. 1250-1264.
8. D. Gamboa, C. Rego, and F. Glover, Implementation analysis of efficient heuristic algorithms for the traveling salesman problem, Comput. Oper. Res. 33 (2006), pp. 1154-1172.
9. F. Gandon, A. Poggi, G. Rimassa, and P. Turci, Multi-agent corporate memory management system, IEEE Intell. Syst. 16 (2002), pp. 699-720.
10. M. Guerini, O. Stock, and M. Zancanaro, A taxonomy of strategies for multimodal persuasive message generation, Appl. Artif. Intell. 21 (2007), pp. 99-136.
11. M. Kianga and D. Fisherc, Selecting the right MBA schools an application of self-organizing map networks, Expert Syst. Appl. 35 (2008), pp. 946-955.
12. O. Kwona, J.M. Shinb, and S.W. Kimc, Context-aware multi-agent approach to pervasive negotiation support systems, Expert Syst. Appl. 31 (2006), pp. 275-285.
13. K. Leung, H. Jin, and Z. Xu, An expanding self-organizing neural network for the traveling salesman problem, Neurocomputing 62 (2004), pp. 267-292.
14. H.M. Avilanoz and M. Cox, Case-based plan adaptation: An analysis and review (special issue on ambient intelligence), IEEE Intell. Syst. 23 (2008), pp. 75-81.
15. M. Shiomi, T. Kanda, H. Ishiguro, and N. Hagita, Interactive humanoid robots for a science museum, IEEE Intell. Syst. 22 (2007), pp. 25-32.
16. L. Spalazzi, A survey on case-based planning, Artif. Intell. Rev. 16 (2001), pp. 3-36.
17. P. Vrba, F. Mačurek, andV. Márík, Using radio frequency identification in agent-based control systems for industrial applications, Eng. Appl. Artif. Intell. 21 (2008), pp. 331-342.