-
1
-
-
0036531878
-
Multiagent learning using a variable learning rate
-
Bowling, M. H., & Veloso, M. M. (2002). Multiagent learning using a variable learning rate. Artificial Intelligence, 136(2), 215-250.
-
(2002)
Artificial Intelligence
, vol.136
, Issue.2
, pp. 215-250
-
-
Bowling, M.H.1
Veloso, M.M.2
-
3
-
-
0004251138
-
-
Cambridge, UK: Cambridge University Press
-
Brams, S. J. (1994) Theory of moves. Cambridge, UK: Cambridge University Press.
-
(1994)
Theory of moves
-
-
Brams, S.J.1
-
6
-
-
1942421183
-
Awesome: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents
-
Conitzer, V., &Sandholm, T. (2003). Awesome: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents. In ICML, (pp. 83-90).
-
(2003)
ICML
, pp. 83-90
-
-
Conitzer, V.1
Sandholm, T.2
-
7
-
-
31844455339
-
Learning to compete, compromise, and cooperate in repeated general-sum games
-
Crandall, J. W., & Goodrich, M. A. (2005). Learning to compete, compromise, and cooperate in repeated general-sum games. In Proceedings of the nineteenth international conference on machine learning, pp. 161-168.
-
(2005)
Proceedings of the nineteenth international conference on machine learning
, pp. 161-168
-
-
Crandall, J.W.1
Goodrich, M.A.2
-
8
-
-
33749245241
-
How to combine expert (and novice) advice when actions impact the environment?
-
de Parias, D. P., & Megiddo, N. (2003). How to combine expert (and novice) advice when actions impact the environment? In NIPS.
-
(2003)
NIPS
-
-
de Parias, D.P.1
Megiddo, N.2
-
10
-
-
1942517280
-
Correlated q-learning
-
Greenwald, A. R., & Hall, K. (2003). Correlated q-learning. In ICML, pp. 242-249.
-
(2003)
ICML
, pp. 242-249
-
-
Greenwald, A.R.1
Hall, K.2
-
11
-
-
9444256279
-
A general class of no-regret learning algorithms and game-theoretic equilibria
-
Greenwald, A. R., & Jafari, A. (2003). A general class of no-regret learning algorithms and game-theoretic equilibria. In COLT, pp. 2-12.
-
(2003)
COLT
, pp. 2-12
-
-
Greenwald, A.R.1
Jafari, A.2
-
13
-
-
0038344583
-
Geometric algorithms for online optimization
-
Technical Report MIT-LCS-TR-861, MIT Laboratory for Computer Science
-
Kalai, A., & Vempala, S. (2002). Geometric algorithms for online optimization. Technical Report MIT-LCS-TR-861, MIT Laboratory for Computer Science.
-
(2002)
-
-
Kalai, A.1
Vempala, S.2
-
14
-
-
34249679753
-
Learning of coordination in cooperative multiagent systems using commitment sequences
-
Kapetanakis, S., Kudenko, D., & Strens, M. (2004). Learning of coordination in cooperative multiagent systems using commitment sequences. Artificial Intelligence and the Simulation of Behavior, 1(5).
-
(2004)
Artificial Intelligence and the Simulation of Behavior
, vol.1
, Issue.5
-
-
Kapetanakis, S.1
Kudenko, D.2
Strens, M.3
-
16
-
-
85149834820
-
Markov games as a framework for multi-agent reinforcement learning
-
San Mateo, CA: Morgan Kaufmann
-
Littman, M. L. (1994). Markov games as a framework for multi-agent reinforcement learning. In Proceedings of the eleventh international conference on machine learning, (pp. 157-163). San Mateo, CA: Morgan Kaufmann.
-
(1994)
Proceedings of the eleventh international conference on machine learning
, pp. 157-163
-
-
Littman, M.L.1
-
18
-
-
80053136974
-
Implicit negotiation in repeated games
-
Littman, M. L., & Stone, P. (2001). Implicit negotiation in repeated games. In Intelligent agents VIII: Agent theories, architecture, and languages, pp. 393-404.
-
(2001)
Intelligent agents VIII: Agent theories, architecture, and languages
, pp. 393-404
-
-
Littman, M.L.1
Stone, P.2
-
19
-
-
9544234477
-
A polynomial-time nash equilibrium algorithm for repeated games
-
Littman, M. L., & Stone, P. (2005). A polynomial-time nash equilibrium algorithm for repeated games. Decision Support System, 39, 55-66.
-
(2005)
Decision Support System
, vol.39
, pp. 55-66
-
-
Littman, M.L.1
Stone, P.2
-
21
-
-
26444601262
-
Cooperative multi-agent learning: The state of the art
-
Panait, L., & Luke, S. (2005). Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3), 387-434.
-
(2005)
Autonomous Agents and Multi-Agent Systems
, vol.11
, Issue.3
, pp. 387-434
-
-
Panait, L.1
Luke, S.2
-
22
-
-
0030050933
-
Multiagent reinforcement learning and iterated prisoner's dilemma
-
Sandholm, T. W., & Crites, R. H. ( 1995). Multiagent reinforcement learning and iterated prisoner's dilemma. Biosystems Journal, 37, 147-166.
-
(1995)
Biosystems Journal
, vol.37
, pp. 147-166
-
-
Sandholm, T.W.1
Crites, R.H.2
-
23
-
-
0542374968
-
Learning with friends and foes
-
Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers
-
Sekaran, M., & Sen, S. (1994). Learning with friends and foes. In Sixteenth annual conference of the cognitive science society, (pp. 800-805). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
-
(1994)
Sixteenth annual conference of the cognitive science society
, pp. 800-805
-
-
Sekaran, M.1
Sen, S.2
-
24
-
-
1142268794
-
Towards a pareto-optimal solution in general-sum games
-
New York, NY: ACM Press
-
Sen, S., Mukherjee, R., & Airiau, S. (2003). Towards a pareto-optimal solution in general-sum games. In Proceedings of the second intenational joint conference, on autonomous agents and multiagent systems (pp. 153-160). New York, NY: ACM Press.
-
(2003)
Proceedings of the second intenational joint conference, on autonomous agents and multiagent systems
, pp. 153-160
-
-
Sen, S.1
Mukherjee, R.2
Airiau, S.3
-
25
-
-
0013327463
-
A general class of adaptive strategies
-
Mas-Colell, A., & Hart, S. (2001). A general class of adaptive strategies. Journal of Economic Theory, 98(1), 26-54.
-
(2001)
Journal of Economic Theory
, vol.98
, Issue.1
, pp. 26-54
-
-
Mas-Colell, A.1
Hart, S.2
-
26
-
-
34249699690
-
Nash convergence of gradient dynamics in general-sum games
-
Singh, S. P., Kearns, M. J., & Mansour, Y. (2000) Nash convergence of gradient dynamics in general-sum games. In UAI, pp. 541-548.
-
(2000)
UAI
, pp. 541-548
-
-
Singh, S.P.1
Kearns, M.J.2
Mansour, Y.3
-
27
-
-
84880910706
-
Satisficing and learning cooperation in the prisoner's dilemma
-
Stimpson, J. L., Goodrich, M. A., & Walters, L. C. (2001) Satisficing and learning cooperation in the prisoner's dilemma. In Proceedings of the seventeenth international joint conference on artificial intelligence, pp. 535-540.
-
(2001)
Proceedings of the seventeenth international joint conference on artificial intelligence
, pp. 535-540
-
-
Stimpson, J.L.1
Goodrich, M.A.2
Walters, L.C.3
-
28
-
-
28544446213
-
Evolutionary game theory and multi-agent reinforcement learning
-
Tuyls, K., & Nowé, A. (2006). Evolutionary game theory and multi-agent reinforcement learning. The Knowledge Engineering Review, 20(1), 63-90.
-
(2006)
The Knowledge Engineering Review
, vol.20
, Issue.1
, pp. 63-90
-
-
Tuyls, K.1
Nowé, A.2
-
29
-
-
84943265381
-
-
Verbeeck, K., Nowé, A., Lenaerts, T., & Parentm, J. (2002). Learning to reach the pareto optimal nash equilibrium as a team. In LNAI 2557: Proceedings of the fifteenth Australian joint conference on artificial intelligence, pp. 407-418). Springer-Verlag.
-
Verbeeck, K., Nowé, A., Lenaerts, T., & Parentm, J. (2002). Learning to reach the pareto optimal nash equilibrium as a team. In LNAI 2557: Proceedings of the fifteenth Australian joint conference on artificial intelligence, Vol. (pp. 407-418). Springer-Verlag.
-
-
-
-
30
-
-
0346502047
-
Predicting the expected behavior of agents that learn about agents: The CLRI framework
-
Vidal, J. M., & Durfee, E. H. (2003). Predicting the expected behavior of agents that learn about agents: the CLRI framework. Autonomous Agents and Multi-Agent Systems, 6(1), 77-107.
-
(2003)
Autonomous Agents and Multi-Agent Systems
, vol.6
, Issue.1
, pp. 77-107
-
-
Vidal, J.M.1
Durfee, E.H.2
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