메뉴 건너뛰기




Volumn 22, Issue , 2004, Pages 353-384

Existence of multiagent equilibria with limited agents

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GAME THEORY; INTELLIGENT AGENTS; LEARNING ALGORITHMS; LEARNING SYSTEMS; SOFTWARE AGENTS;

EID: 27344450680     PISSN: 10769757     EISSN: 10769757     Source Type: Journal    
DOI: 10.1613/jair.1332     Document Type: Article
Times cited : (28)

References (52)
  • 4
    • 0036531878 scopus 로고    scopus 로고
    • Multiagent learning using a variable learning rate
    • Bowling, M., & Veloso, M. (2002). Multiagent learning using a variable learning rate. Artificial Intelligence, 136, 215-250.
    • (2002) Artificial Intelligence , vol.136 , pp. 215-250
    • Bowling, M.1    Veloso, M.2
  • 11
    • 38249006045 scopus 로고
    • Bounded versus unbounded rationality: The tyranny of the weak
    • Gilboa, I., & Samet, D. (1989). Bounded versus unbounded rationality: The tyranny of the weak. Games and Economic Behavior, 213-221.
    • (1989) Games and Economic Behavior , pp. 213-221
    • Gilboa, I.1    Samet, D.2
  • 18
    • 0000619048 scopus 로고
    • Extensive games and the problem of information
    • Kuhn, H. W., & Tucker, A. W. (Eds.), Princeton University Press. Reprinted in (Kuhn, 1997)
    • Kuhn, H. W. (1953). Extensive games and the problem of information. In Kuhn, H. W., & Tucker, A. W. (Eds.), Contributions to the Theory of Games II, pp. 193-216. Princeton University Press. Reprinted in (Kuhn, 1997).
    • (1953) Contributions to the Theory of Games II , pp. 193-216
    • Kuhn, H.W.1
  • 20
    • 0035501436 scopus 로고    scopus 로고
    • Bargaining with limited computation: Deliberation equilibrium
    • Larson, K., & Sandholm, T. (2001). Bargaining with limited computation: Deliberation equilibrium. Artificial Intelligence, 132(2), 183-217.
    • (2001) Artificial Intelligence , vol.132 , Issue.2 , pp. 183-217
    • Larson, K.1    Sandholm, T.2
  • 25
    • 0029752592 scopus 로고    scopus 로고
    • Average reward reinforcement learning: Foundations, algorithms, and empirical results
    • Mahadevan, S. (1996). Average reward reinforcement learning: Foundations, algorithms, and empirical results. Machine Learning, 22, 159-196.
    • (1996) Machine Learning , vol.22 , pp. 159-196
    • Mahadevan, S.1
  • 29
    • 0027684215 scopus 로고
    • Prioritized sweeping: Reinforcement learning with less data and less time
    • Moore, A. W., & Atkeson, C. G. (1993). Prioritized sweeping: Reinforcement learning with less data and less time. Machine Learning, 13, 103-130.
    • (1993) Machine Learning , vol.13 , pp. 103-130
    • Moore, A.W.1    Atkeson, C.G.2
  • 30
    • 0002021736 scopus 로고
    • Equilibrium points in n-person games
    • Reprinted in (Kuhn, 1997)
    • Nash, Jr., J. F. (1950). Equilibrium points in n-person games. PNAS, 36, 48-49. Reprinted in (Kuhn, 1997).
    • (1950) PNAS , vol.36 , pp. 48-49
    • Nash Jr., J.F.1
  • 34
    • 0345108843 scopus 로고    scopus 로고
    • Games with procedurally rational players
    • McMaster University, Department of Economics
    • Osborne, M. J., & Rubinstein, A. (1997). Games with procedurally rational players. Working papers 9702, McMaster University, Department of Economics.
    • (1997) Working Papers , vol.9702
    • Osborne, M.J.1    Rubinstein, A.2
  • 37
    • 0001402950 scopus 로고
    • An iterative method of solving a game
    • Reprinted in (Kuhn, 1997)
    • Robinson, J. (1951). An iterative method of solving a game. Annals of Mathematics, 54, 296-301. Reprinted in (Kuhn, 1997).
    • (1951) Annals of Mathematics , vol.54 , pp. 296-301
    • Robinson, J.1
  • 38
    • 0018922522 scopus 로고
    • Existence and uniqueness of equilibrium points for concave n-person games
    • Rosen, J. B. (1965). Existence and uniqueness of equilibrium points for concave n-person games. Econometrica, 33, 520-534.
    • (1965) Econometrica , vol.33 , pp. 520-534
    • Rosen, J.B.1
  • 41
    • 0000392613 scopus 로고
    • Stochastic games
    • Reprinted in (Kuhn, 1997)
    • Shapley, L. S. (1953). Stochastic games. PNAS, 39, 1095-1100. Reprinted in (Kuhn, 1997).
    • (1953) PNAS , vol.39 , pp. 1095-1100
    • Shapley, L.S.1
  • 42
    • 0002298346 scopus 로고
    • From substantive to procedural rationality
    • Latis, S. J. (Ed.), Cambridge University Press, New York
    • Simon, H. A. (1976). From substantive to procedural rationality. In Latis, S. J. (Ed.), Methods and Appraisals in Economics, pp. 129-148. Cambridge University Press, New York.
    • (1976) Methods and Appraisals in Economics , pp. 129-148
    • Simon, H.A.1
  • 44
    • 0033901602 scopus 로고    scopus 로고
    • Convergence results for single-step on-policy reinforcement-learning algorithms
    • Singh, S., Jaakkola, T., Littman, M. L., & Szepesvári, C. (2000). Convergence results for single-step on-policy reinforcement-learning algorithms. Machine Learning.
    • (2000) Machine Learning
    • Singh, S.1    Jaakkola, T.2    Littman, M.L.3    Szepesvári, C.4
  • 48
    • 0004196515 scopus 로고    scopus 로고
    • Adversarial reinforcement learning
    • Carnegie Mellon University. Unpublished
    • Uther, W., & Veloso, M. (1997). Adversarial reinforcement learning. Tech. rep., Carnegie Mellon University. Unpublished.
    • (1997) Tech. Rep.
    • Uther, W.1    Veloso, M.2
  • 49
    • 23144434851 scopus 로고    scopus 로고
    • Ph.D. thesis, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA. Available as technical report CMU-CS-02-169
    • Uther, W. T. B. (2002). Tree Based Hierarchical Reinforcement Learning. Ph.D. thesis, Computer Science Department, Carnegie Mellon University, Pittsburgh, PA. Available as technical report CMU-CS-02-169.
    • (2002) Tree Based Hierarchical Reinforcement Learning
    • Uther, W.T.B.1
  • 52
    • 0012252296 scopus 로고
    • Tight performance bounds on greedy policies based on imperfect value functions
    • College of Computer Science, Northeastern University
    • Williams, R. J., & Baird, L. C. (1993). Tight performance bounds on greedy policies based on imperfect value functions. Technical report, College of Computer Science, Northeastern University.
    • (1993) Technical Report
    • Williams, R.J.1    Baird, L.C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.