Conjectural Equilibrium in Multiagent Learning
Open accessThe claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Artificial intelligence: a modern approach
Kumar, D. A., Balasubramanian, S., Byeon, D. H., & Manerkar, P. G. V. (1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 22,182 · see citing works
Artificial intelligence: A modern approach
Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,726 · see citing works
Reinforcement Learning: A Survey
Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996) · Journal of Artificial Intelligence Research · doi:10.1613/jair.301 · Cited by 8,972 · see citing works
Markov Games as a Framework for Multi-Agent Reinforcement Learning
Littman, M. L. (1994) · International Conference on Machine Learning · doi:10.1016/b978-1-55860-335-6.50027-1 · Cited by 3,406 · see citing works
Capital-Labor Substitution and Economic Efficiency
Arrow, K. J., Chenery, H. B., Minhas, B. S., & Solow, R. M. H. (1961) · The Review of Economics and Statistics · doi:10.2307/1927286 · Cited by 2,229 · see citing works
Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents
Tan, M. (1993) · Elsevier eBooks · doi:10.1016/b978-1-55860-307-3.50049-6 · Cited by 1,860 · see citing works
Handbook of Global Optimization
Horst, R., & Pardalos, P. M. (1995) · Nonconvex optimization and its applications · doi:10.1007/978-1-4615-2025-2 · Cited by 1,638 · see citing works
Game Theory for Applied Economists
Gibbons, R. S. (1992) · Princeton University Press eBooks · doi:10.1515/9781400835881 · Cited by 1,486 · see citing works
Introduction to Global Optimization
Horst, R., Pardalos, P. M., & Thoại, N. V. (2000) · Nonconvex optimization and its applications · doi:10.1007/978-1-4615-0015-5 · Cited by 1,232 · see citing works
Competitive Markov Decision Processes
Filar, J. A., & Vrieze, K. (1996) · Springer eBooks · doi:10.1007/978-1-4612-4054-9 · Cited by 1,202 · see citing works
The dynamics of reinforcement learning in cooperative multiagent systems
Claus, C., & Boutilier, C. E. (1998) · Cited by 1,106 · see citing works
de Mélo, J., Shoven, J. B., & Whalley, J. (1993) · The Economic Journal · doi:10.2307/2234492 · Cited by 1,020 · see citing works
Game Theory for Applied Economists
Gibbons, R. D. (1992) · Princeton University Press eBooks · doi:10.2307/j.ctvcmxrzd · Cited by 929 · see citing works
Spivak, M. (2018) · CRC Press eBooks · doi:10.1201/9780429501906 · Cited by 812 · see citing works
Multiagent Reinforcement Learning: Theoretical Framework and an Algorithm
Hu, J., & Wellman, M. P. (1998) · Cited by 759 · see citing works
Self-citationYoung, H. P. (1996) · The Journal of Economic Perspectives · doi:10.1257/jep.10.2.105 · Cited by 540 · see citing works
Wellman, M. P. (1993) · Journal of Artificial Intelligence Research · doi:10.1613/jair.2 · Cited by 527 · see citing works
Self-citationFudenberg, D., & Levine, D. K. (1993) · Econometrica · doi:10.2307/2951716 · Cited by 523 · see citing works
Glycopantis, D., & Takayama, A. (1976) · Economica · doi:10.2307/2553143 · Cited by 422 · see citing works
Social Stability and Equilibrium
Gilboa, I., & Matsui, A. (1991) · Econometrica · doi:10.2307/2938230 · Cited by 347 · see citing works
Adaptive and sophisticated learning in normal form games
Milgrom, P., & Roberts, J. H. (1991) · Games and Economic Behavior · doi:10.1016/0899-8256(91)90006-z · Cited by 343 · see citing works
On the emergence of social conventions: modeling, analysis, and simulations
Shoham, Y., & Tennenholtz, M. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00028-3 · Cited by 290 · see citing works
Starting Point Bias in Contingent Valuation Bidding Games
Boyle, K., Bishop, R. C., & Welsh, M. (1985) · Land Economics · doi:10.2307/3145811 · Cited by 263 · see citing works
The Stability of a Competitive Economy: A Survey Article
Negishi, T. (1962) · Econometrica · doi:10.2307/1909319 · Cited by 252 · see citing works
Knowledge and Equilibrium in Games
Brandenburger, A. M. (1992) · The Journal of Economic Perspectives · doi:10.1257/jep.6.4.83 · Cited by 168 · see citing works
The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes
Cheng, J. Q., & Wellman, M. P. (1998) · Computational Economics · doi:10.1023/a:1008654125853 · Cited by 165 · see citing works
Self-citationIntroduction to Global Optimization.
Tofallis, C., Horst, R., Padalos, P. M., & Thoai, N. V. (1996) · Journal of the Operational Research Society · doi:10.2307/3010143 · Cited by 157 · see citing works
Dynamics of computational ecosystems
Kephart, J. O., Hogg, T., & Huberman, B. A. (1989) · Physical Review A · doi:10.1103/physreva.40.404 · Cited by 150 · see citing works
Learning to coordinate actions in multi-agent systems
Weiß, G. (1993) · International Joint Conference on Artificial Intelligence · Cited by 110 · see citing works
Applying General EquilibriumPreprint
Shoven, J. B., & Whalley, J. (1992) · RePEc: Research Papers in Economics · Cited by 98 · see citing works
A computational market model for distributed configuration design
Wellman, M. P. (1995) · Artificial intelligence for engineering design analysis and manufacturing · doi:10.1017/s089006040000216x · Cited by 94 · see citing works
Self-citationOnline learning about other agents in a dynamic multiagent system
Hu, J., & Wellman, M. P. (1998) · Proceedings of the second international conference on Autonomous agents - AGENTS '98 · doi:10.1145/280765.280839 · Cited by 84 · see citing works
Self-citationExercises in Conjectural Equilibria
Hahn, F. H. (1978) · Palgrave Macmillan UK eBooks · doi:10.1007/978-1-349-03917-3_4 · Cited by 77 · see citing works
Exercises in Conjectural Equilibria
Hahn, F. H. (1977) · Scandinavian Journal of Economics · doi:10.2307/3439508 · Cited by 71 · see citing works
Takayama, A. (1991) · Cited by 60 · see citing works
A Simple Computational Market for Network Information Services
Mullen, T., & Wellman, M. P. (1995) · Cited by 59 · see citing works
Self-citationLearning nested agent models in an information economy
Vidal, J. M., & Durfee, E. H. (1998) · Journal of Experimental & Theoretical Artificial Intelligence · doi:10.1080/095281398146770 · Cited by 47 · see citing works
On the Gains and Losses of Speculation in Equilibrium Markets
Sandholm, T., & Ygge, F. (1997) · Cited by 45 · see citing works
Agents Learning about Agents: A Framework and Analysis
Vidal, M. C., & Durfee, E. H. (1997) · Cited by 37 · see citing works
Self-fulfilling Bias in Multiagent Learning
Hu, J., & Wellman, M. P. (1996) · Cited by 34 · see citing works
Self-citationLearning Conventions in Multiagent Stochastic Domains using Likelihood EstimatesPreprint
Boutilier, C. E. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1302.3561 · Cited by 25 · see citing works
IJCAI-95 Workshop on Adaptation and Learning in Multiagent Systems
Sen, S. (1996) · AI Magazine · doi:10.1609/aimag.v17i1.1215 · Cited by 15 · see citing works
A NOTE ON THE EXISTENCE OF STARTING POINT BIAS IN ITERATIVE BIDDING GAMES
Samples, K. C., & Samples, K. C. (1985) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.32510 · Cited by 14 · see citing works
Flagged first, then by citations
3 of the 46 references couldn’t be matched to a known paper.
Research works printed but not linked: 6
- Cliff, D. (1998). Evolving parameter sets for adaptive trading agents in continuous double-auction markets. Agents-98 Workshop on Artificial Societies and Computational Markets, (pp. 38-47). Minneapolis, MN.
- Fudenberg, D. & Tirole, J. (1991). Game Theory. MIT Press.
- Grefenstette, J.J., et al. (Eds.). (1996). AAAI Spring Symposium on Adaptation, Coevolution, and Learning in Multiagent Systems. AAAI Press.
- Hahn, F.H. (1977). Exercises in conjectural equilibrium analysis. Scandinavian Journal of Economics, 79, 210-226.
- Ono, N. & Fukumoto, K. (1996). Multi-agent reinforcement learning: A modular approach. Second International Conference on Multiagent Systems, (pp. 252-258). Kyoto, Japan.
- Sen, S. (Ed.). (1997). AAAI-97 Workshop on Multiagent Learning. AAAI Press.
Cited by
Sorted by citations
Cooperative Multi-Agent Learning: The State of the Art
Panait, L., & Luke, S. (2005) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-005-2631-2 · Cited by 1,237 · see citing works
Nash Q-Learning for General-Sum Stochastic Games
Hu, J., Wellman, M. P., & Boutilier, C. (2003) · Cited by 909 · see citing works
Self-citationCombinatorial auctions for supply chain formation
Walsh, W. E., Wellman, M. P., & Ygge, F. (2000) · ACM Conference on Electronic Commerce (EC) · doi:10.1145/352871.352900 · Cited by 175 · see citing works
Self-citationDecentralized Markets versus Central Control: A Comparative Study
Ygge, F., & Akkermans, H. (1999) · Journal of Artificial Intelligence Research · doi:10.1613/jair.627 · Cited by 119 · see citing works
A Survey on Applications of Model-Free Strategy Learning in Cognitive Wireless Networks
Wang, W., Kwasinski, A., Niyato, D. T., & Han, Z. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2539923 · Cited by 90 · see citing works
An Overview of Cooperative and Competitive Multiagent Learning
Hoen, P. J. ’., Tuyls, K., Panait, L., Luke, S., & Poutré, J. A. L. (2006) · Lecture notes in computer science · doi:10.1007/11691839_1 · Cited by 78 · see citing works
Chen, X., Zhao, Z., & Zhang, H. (2012) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2012.178 · Cited by 73 · see citing works
Reaching pareto-optimality in prisoner’s dilemma using conditional joint action learning
Banerjee, D., & Sen, S. (2007) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-007-0020-8 · Cited by 53 · see citing works
An adaptive agent bidding strategy based on stochastic modeling
Park, S., Durfee, E. H., & Birmingham, W. P. (1999) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/301136.301181 · Cited by 53 · see citing works
Game theoretical applications for multi-agent systems
Pendharkar, P. C. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.07.017 · Cited by 50 · see citing works
Agents in E-Commerce: State of the Art
He, M., & Leung, H.-F. (2002) · Knowledge and Information Systems · doi:10.1007/s101150200007 · Cited by 45 · see citing works
Learning about other agents in a dynamic multiagent system
Hu, J., & Weliman, M. P. (2001) · Cognitive Systems Research · doi:10.1016/s1389-0417(01)00016-x · Cited by 43 · see citing works
Self-citationStackelberg Contention Games in Multi-User NetworksPreprint
Park, J., & van der Schaar, M. (2012) · Cited by 41 · see citing works
An Elementary Introduction to Auctions
Rothkopf, M. H., & Park, S. (2001) · INFORMS Journal on Applied Analytics · doi:10.1287/inte.31.7.83.9637 · Cited by 41 · see citing works
Stackelberg Contention Games in Multiuser Networks
Park, J., & van der Schaar, M. (2009) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/2009/305978 · Cited by 32 · see citing works
Learning in Network Contexts: Experimental Results from Simulations
Greenwald, A., Friedman, E. J., & Shenker, S. (2001) · Games and Economic Behavior · doi:10.1006/game.2000.0835 · Cited by 32 · see citing works
An Elementary Introduction to Auctions
Rothkopf, M. H., & Park, S. (2001) · INFORMS Journal on Applied Analytics · doi:10.1287/inte.31.6.83.9637 · Cited by 32 · see citing works
REINFORCEMENT LEARNING IN MARKOVIAN EVOLUTIONARY GAMES
Borkar, V. S. (2002) · Advances in Complex Systems · doi:10.1142/s0219525902000535 · Cited by 31 · see citing works
Autonomous Adaptive Agents for Single Seller Sealed Bid Auctions
Bagnall, A. J., & Toft, I. (2005) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-005-4948-2 · Cited by 28 · see citing works
Market protocols for decentralized supply chain formation
Walsh, W. E., & Wellman, M. P. (2001) · Cited by 29 · see citing works
Self-citationConjectural Equilibrium in Multiuser Power Control Games
Su, Y., & van der Schaar, M. (2009) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2009.2020395 · Cited by 25 · see citing works
YinYang Bipolar Relativity - A Unifying Theory of Nature, Agents and Life Science
Zhang, W.-R. (2009) · International Joint Conferences on Bioinformatics, Systems Biology and Intelligent Computing · doi:10.1109/ijcbs.2009.90 · Cited by 25 · see citing works
Multiagent Cooperative Search for Portfolio Selection
Parkes, D. C., & Huberman, B. A. (2001) · Games and Economic Behavior · doi:10.1006/game.2000.0799 · Cited by 24 · see citing works
Game Theory in Signal Processing and Communications
Boche, H., Han, Z., Larsson, E. G., & Jorswieck, E. A. (2009) · EURASIP Journal on Advances in Signal Processing · doi:10.1155/2009/128184 · Cited by 22 · see citing works
Dynamic conjectures in random access networks using bio-inspired learning
Su, Y., & van der Schaar, M. (2010) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2010.100508 · Cited by 22 · see citing works
QoS-Oriented Wireless Routing for Smart Meter Data Collection: Stochastic Learning on Graph
Cao, Y., Duan, D., Cheng, X., Yang, L., & Wei, J. (2014) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2014.2314121 · Cited by 21 · see citing works
Decentralized Organizational Learning: An Experimental Investigation
Blume, A., Duffy, J. F., & Franco, A. M. (2009) · American Economic Review · doi:10.1257/aer.99.4.1178 · Cited by 21 · see citing works
Non-cooperative reinforcement learning based routing in cognitive radio networks
Pourpeighambar, B., Dehghan, M., & Sabaei, M. (2017) · Computer Communications · doi:10.1016/j.comcom.2017.02.013 · Cited by 20 · see citing works
Linearly Coupled Communication Games
Su, Y., & van der Schaar, M. (2011) · IEEE Transactions on Communications · doi:10.1109/tcomm.2011.062111.090417 · Cited by 18 · see citing works
Emergent properties of a market-based digital library with strategic agents
Park, S., Durfee, E. H., & Birmingham, W. P. (2002) · International Conference on Multi Agent Systems · doi:10.1109/icmas.1998.699054 · Cited by 18 · see citing works
Use of Markov Chains to Design an Agent Bidding Strategy for Continuous Double Auctions
Park, S., Durfee, E. H., & Birmingham, W. P. (2004) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1466 · Cited by 16 · see citing works
On market-inspired approaches to propositional satisfiability
Walsh, W. E., Yokoo, M., Hirayama, K., & Wellman, M. P. (2003) · Artificial Intelligence · doi:10.1016/s0004-3702(02)00386-7 · Cited by 16 · see citing works
Self-citationThe theory and experiments of designing cooperative intelligent systems
Pendharkar, P. C. (2005) · Decision Support Systems · doi:10.1016/j.dss.2005.05.028 · Cited by 15 · see citing works
Emergent Properties of a Market-based Digital Library with Strategic Agents
Park, S., Durfee, E. H., & Birmingham, W. P. (2000) · Autonomous Agents and Multi-Agent Systems · doi:10.1023/a:1010081711284 · Cited by 12 · see citing works
Bidding Strategies in QoS-Aware Cloud Systems Based on N-Armed Bandit Problems
Abundo, M., Valerio, V. D., Cardellini, V., & Presti, F. L. (2014) · IEEE Symposium on Network Cloud Computing and Applications (NCCA) · doi:10.1109/ncca.2014.15 · Cited by 11 · see citing works
Constructing Speculative Demand Functions in Equilibrium Markets
Sandholm, T. (1999) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7gt5kfm · Cited by 11 · see citing works
Conjectural Equilibrium in Water-Filling Games
Su, Y., & van der Schaar, M. (2009) · Globecom · doi:10.1109/glocom.2009.5425333 · Cited by 10 · see citing works
Agent Service for Online Auctions
Hu, J., Reeves, D. M., & Wong, H.-S. (1999) · Cited by 11 · see citing works
Self-citationToward Automated Pricing and Bundling of Information Goods
Brooks, C. H., & Durfee, E. H. (2000) · Cited by 9 · see citing works
Allocating fixed costs using multi-coalition epsilon equilibrium
Pendharkar, P. C. (2021) · International Journal of Production Economics · doi:10.1016/j.ijpe.2021.108174 · Cited by 8 · see citing works
Game-theoretic solution concepts and learning algorithms
Perlaza, S. M., & Lasaulce, S. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9781139524421.009 · Cited by 7 · see citing works
A Multiagent System for Efficient Portfolio Management
López, V. F., Alonso, N., Alonso, L., & Garcı́a, M. N. M. (2010) · Advances in intelligent and soft computing · doi:10.1007/978-3-642-12433-4_7 · Cited by 6 · see citing works
Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
Akbarimajd, A., & Simzan, G. (2014) · International Journal of Computational Intelligence Systems · doi:10.1080/18756891.2014.922814 · Cited by 6 · see citing works
Linearly coupled communication games
Su, Y., & van der Schaar, M. (2010) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2010.5707022 · Cited by 5 · see citing works
Reciprocal learning for cognitive medium access
Chen, X., Zhao, Z., Grace, D., & Zhang, H. (2013) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc.2013.6554544 · Cited by 4 · see citing works
Conjecture-based channel selection game for delay-sensitive users in multi-channel wireless networks
Shiang, H.-P., & van der Schaar, M. (2009) · International Conference on Game Theory for Networks · doi:10.1109/gamenets.2009.5137407 · Cited by 4 · see citing works
Potential-Based Reward Shaping for Knowledge-Based, Multi-Agent Reinforcement Learning
Devlin, S. (2013) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · Cited by 4 · see citing works
An Agent Model for First Price and Second Price Private Value Auctions
Bagnall, A. J., & Toft, I. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-24621-3_23 · Cited by 4 · see citing works
MARLBS: Team Cooperation through Bidding
Sun, R., & Qi, D. (2005) · International Journal of Computational Intelligence Research · doi:10.5019/j.ijcir.2005.22 · Cited by 3 · see citing works
Reciprocally opportunistic spectrum access
Chen, X., Zhang, H., Höyhtyä, M., Lasanen, M., & Palicot, J. (2014) · Transactions on Emerging Telecommunications Technologies · doi:10.1002/ett.2810 · Cited by 3 · see citing works
Computing a self-confirming equilibrium in two-player extensive-form games
Gatti, N., Panozzo, F., & Ceppi, S. (2011) · doi:10.5555/2034396.2034409 · Cited by 3 · see citing works
Teymoori, P., & Boukerche, A. (2023) · Globecom · doi:10.1109/globecom54140.2023.10436929 · Cited by 2 · see citing works
A Semi-Potential for Finite and Infinite Games in Extensive Form
Roux, S. L., & Pauly, A. (2019) · Dynamic Games and Applications · doi:10.1007/s13235-019-00301-7 · Cited by 2 · see citing works
Towards Efficient, Stable, and Fair Random Access Networks: A Conjectural Equilibrium Approach
Su, Y., & van der Schaar, M. (2010) · Globecom · doi:10.1109/glocom.2010.5684242 · Cited by 1 · see citing works
Mathematical programming formulations to compute steady states in two-player extensive-form games
Gatti, N., Panozzo, F., & Ceppi, S. (2010) · Cited by 1 · see citing works
Model of the ZI-C experiment for double auction system
Li, L., Xueying, W., & Guangyu, C. (2011) · International Conference on E-Business and E-Government · doi:10.1109/icebeg.2011.5881340 · Cited by 1 · see citing works
Reciprocal Learning for Energy-Efficient Opportunistic Spectrum Access in Cognitive Radio Networks
Chen, X., Zhao, Z., Wu, J., & Chen, T. (2012) · CRC Press eBooks · doi:10.1201/b13083-7 · Cited by 1 · see citing works
Avoiding deadlock using pricing strategies for networks of intelligent personal assistants
Wilde, P. D., & Lee, L. C. (2002) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.2001.971950 · Cited by 1 · see citing works
Linearly Coupled Communication GamesPreprint
Su, Y., & van der Schaar, M. (2009) · arXiv (Cornell University) · doi:10.48550/arxiv.0908.1613 · Cited by 1 · see citing works
Studies of dynamics of physical agent ecosystems
Moreno, I. M. (2002) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · Cited by 1 · see citing works
Zeng, D. D., & Nissen, M. E. (2004) · The Internet Encyclopedia · doi:10.1002/047148296x.tie084 · Cited by 1 · see citing works
Zheng, Y.-J., Basarab, G. S., & Jordan, D. B. (2002) · PubMed · doi:10.1021/bi015848u
Power Allocation for Cognitive Wireless Mesh Networks by Applying Multi-agent Q-learning ApproachPreprint
Chen, X., Zhao, Z., & Zhang, H. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1102.5400
Chen, X., Zhao, Z., & Zhang, H. (2012) · doi:10.1002/9781118360316.ch7
Learning in Multi-Agent Information Systems - A Survey from IS Perspective
Gurung, A., & Sikora, R. T. (2005) · Journal of the Association for Information Systems
An evolutionary multi-agent system for production scheduling
Pendharkar, P. C. (2005) · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications · doi:10.1109/cca.2005.1507251
Learning from FailurePreprint
Blume, A., & Franco, A. M. (2002) · doi:10.21034/sr.299
The Analysis and Design of Concurrent Learning Algorithms for Cooperative
Panait, L., & Luke, S. (2006)
Designing autonomic wireless multi-hop networks for delay-sensitive applications
Shiang, H.-P. (2009)
Game-Theoretic Opportunistic Spectrum Sharing
Yuan, X., Jalaian, B., Hou, Y. T., Lou, W., Midkiff, S. F., & Kompella, S. (2016) · CRC Press eBooks · doi:10.1201/9781315370422-14
Microeconomic Model Based on MAS Framework: Modeling an Adaptive Producer
Brazdil, P., & Teixeira, F. (2011) · Springer proceedings in mathematics · doi:10.1007/978-3-642-11456-4_9
Agents, Causality, and YinYang Bipolar Relativity
(2011) · IGI Global eBooks · doi:10.4018/978-1-60960-525-4.ch006
Bipolar Sets and YinYang Bipolar Dynamic Logic (BDL)
(2011) · IGI Global eBooks · doi:10.4018/978-1-60960-525-4.ch003
Xu, Y., & Anpalagan, A. (2015) · Springer briefs in electrical and computer engineering · doi:10.1007/978-981-10-0024-9_1
- Authors
- Wellman, M. P., & Hu, J.
- Affiliations
- University of Michigan (US)
- Venue
- Machine Learning
- Published
- 1998-11
- Volume
- 33
- Issue
- 2-3
- Pages
- 179-200
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W2117138095
- Cited by
- 75
- References
- 46
- Citations by year
- 2023: 1 · 2021: 1 · 2019: 1 · 2017: 1 · 2016: 2 · 2015: 1 · 2014: 4 · 2013: 4 · 2012: 4
- FWCI
- 8.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Machine Learning (publishedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Keywords
- multi-agent learning, strategic learning, competitive behavior, convergence
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review