Result 1 to 20 of 50 total
What kinds of human negotiation skill can be acquired by changing negotiation order of bargaining agents? (English)
Salvendy, Gavriel (ed.) et al., Human interface and the management of information. Interacting with information. Symposium on human interface 2011, held as Part of HCI international 2011, Orlando, FL, USA, July 9‒14, 2011. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-21668-8/pbk). Lecture Notes in Computer Science 6772, 335-344 (2011).
1
Towards generalization by identification-based XCS in multi-steps problem (English)
NaBIC, 389-394 (2011).
2
Adaptive mutation depending on program size in asynchronous program evolution (English)
NaBIC, 433-438 (2011).
3
What kinds of human negotiation skill can be acquired by changing negotiation order of bargaining agents? (English)
HCI (12), 335-344 (2011).
4
Toward strategic human skill development through human and agent interaction: improving negotiation skill by interacting with bargaining agent. (English)
J. Adv. Comput. Intell. Intell. Inform. 14, No. 7, 831-839 (2010).
5
Hybrid directional-biased evolutionary algorithm for multi-objective optimization. (English)
Schaefer, Robert (ed.) et al., Parallel problem solving from nature ‒ PPSN XI. 11th international conference, Kraków, Poland, September 11‒15, 2010. Proceedings, Part II. Berlin: Springer (ISBN 978-3-642-15870-4/pbk). Lecture Notes in Computer Science 6239, 121-130 (2010).
6
Learning multiple band-pass filters for sleep stage estimation: towards care support for aged persons (English)
IEICE Transactions 93-B, No. 4, 811-818 (2010).
7
Hybrid directional-biased evolutionary algorithm for multi-objective optimization (English)
PPSN (2), 121-130 (2010).
8
Evolutionary optimization for hub and spoke network based on demand and operation (English)
NaBIC, 678-683 (2010).
9
Dynamic matching range in exemplar-based learning classifier system (English)
IEEE Congress on Evolutionary Computation, 1-8 (2010).
10
Exemplar generalization in reinforcement learning: improving performance with fewer exemplars. (English)
J. Adv. Comput. Intell. Intell. Inform. 13, No. 6, 683-690 (2009).
11
Time horizon generalization in reinforcement learning: generalizing multiple Q-tables in Q-learning agents. (English)
J. Adv. Comput. Intell. Intell. Inform. 13, No. 6, 667-674 (2009).
12
Is gradient descent update consistent with accuracy-based learning classifier system? (English)
J. Adv. Comput. Intell. Intell. Inform. 13, No. 6, 640-648 (2009).
13
Analyzing strength-based classifier system from reinforcement learning perspective. (English)
J. Adv. Comput. Intell. Intell. Inform. 13, No. 6, 631-639 (2009).
14
From my agent to our agent: Exploring collective adaptive agent via Barnga. (English)
Nicholson, Ann (ed.) et al., AI 2009: Advances in artificial intelligence. 22nd Australasian joint conference, Melbourne, Australia, December 1‒4, 2009. Proceedings. Berlin: Springer (ISBN 978-3-642-10438-1/pbk). Lecture Notes in Computer Science 5866. Lecture Notes in Artificial Intelligence, 41-51 (2009).
15
From my agent to our agent: exploring collective adaptive agent via barnga (English)
Australasian Conference on Artificial Intelligence, 41-51 (2009).
16
Learning classifier systems. 10th international workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th international workshop, IWLCS 2007, London, UK, July 8, 2007. Revised selected papers. (English)
Lecture Notes in Computer Science 4998. Lecture Notes in Artificial Intelligence. Berlin: Springer (ISBN 978-3-540-88137-7/pbk). x, 307~p. EUR~52.38 (2008).
17
A partitioned random network agent model for organizational sectionalism studies. (English)
Sakurai, Akito (ed.) et al., New frontiers in artificial intelligence. JSAI 2003 and JSAI 2004 conferences and workshops, Niigata, Japan, June 23‒27, 2003 and Kanazawa, Japan, May 31‒June 4, 2004. Revised selected papers. Berlin: Springer (ISBN 978-3-540-71008-0/pbk). Lecture Notes in Computer Science 3609. Lecture Notes in Artificial Intelligence, 114-125 (2007).
18
Exploring quantitative evaluation criteria for service and potentials of new service in transportation: Analyzing transport networks of railway, subway, and waterbus. (English)
Yin, Hujun (ed.) et al., Intelligent data engineering and automated learning ‒ IDEAL 2007. 8th international conference, Birmingham, UK, December 16‒19, 2007. Proceedings. Berlin: Springer (ISBN 978-3-540-77225-5/pbk). Lecture Notes in Computer Science 4881, 1122-1130 (2007).
19
Analysis on transport networks of railway, subway and waterbus in Japan (English)
Emergent Intelligence of Networked Agents, 99-113 (2007).
20
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