Kagan Tumer's Publications

• Sorted by Date • Classified by Publication Type • Classified by Research Category •

Classified by Research Category

• Collectives • Multiagent Systems • Complex Systems • Distributed Reinforcement Learning • Intelligent Prognostics • Adaptive Routing • Evolutionary Algorithms • Optimization • Distributed Control • Economics/Game Theory • Classifier Ensembles • Bayes Error Estimation • Other Topics •

Collectives

• Collectives and the Design of Complex Systems, K. Tumer and D. Wolpert, editors. Springer, New York, 2004.
  Available from the publisher's website.
  ISBN 0-387-40165-2
  Details     Download: (unavailable)


• A Survey of Collectives. K. Tumer and D. Wolpert. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pp. 1–42, Springer, 2004.
  Details     Download: [pdf] (259.7kB )  


• Overcoming Communication Restrictions in Collectives. K. Tumer and A. Agogino. In Proceedings of the International Joint Conference on Neural Networks, Budapest, Hungary, July 2004.
  Details     Download: [pdf] (114.4kB )  


• Coordination in Large Collectives. K. Tumer and D. Wolpert. In Y. Bar-Yam, editors, Fifth International Conference on Complex Systems, Perseus Books, 2004.
  Details     Download: (unavailable)


• Improving Search Algorithms by Using Intelligent Coordinates. D. H. Wolpert, K. Tumer, and E. Bandari. Physical Review E, 69, 2004.
  Details     Download: [pdf] (107.0kB )  


• Team Formation and Communication Restrictions in Collectives. A. Agogino and K. Tumer. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Australia, July 2003. (short paper)
  Details     Download: [pdf] (81.5kB )  


• Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers. K. Tumer and J. Lawson. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Australia, July 2003. (short paper)
  Details     Download: (unavailable)


• Collective Intelligence, Data Routing and Braess' Paradox. D. H. Wolpert and K. Tumer. Journal of Artificial Intelligence Research, 16:359–387, 2002.
  Details     Download: [pdf] (226.9kB )  


• Optimal Payoff Functions for Members of Collectives. D. H. Wolpert and K. Tumer. In F. Schweitzer, editors, Modeling Complexity in Economic and Social Systems, pp. 355–369, World Scientific, 2002.
  Details     Download: (unavailable)


• Beyond Mechanism Design. D. H. Wolpert and K. Tumer. In ICM Game Theory Conference, ``Heterogeneous and Social Games'' Special Session, Qingdao, China, August 2002.
  Details     Download: (unavailable)


• Overview of Design of Collectives. D. H. Wolpert and K. Tumer. In Robosphere 2002: Self Sustaining Robotic Ecologies, pp. 11–16, Moffett Field, CA., November 2002.
  Details     Download: (unavailable)


• Optimal Payoff Functions for Members of Collectives. D. H. Wolpert and K. Tumer. Advances in Complex Systems, 4(2/3):265–279, 2001.
  Details     Download: [pdf] (276.5kB )  


• Optimal Reward Functions in Distributed Reinforcement Learning. D. H. Wolpert and K. Tumer. In Proceedings of the Second Asia-Pacific Conference on Intelligent Agent Technology (IAT-2001), Maebashi City, Japan, October 2001.
  Details     Download: (unavailable)


• Collective Intelligence and Braess' Paradox. K. Tumer and D. H. Wolpert. In Proceedings of the Seventeenth National Conference on Artificial Intelligence, pp. 104–109, Austin, TX, 2000.
  Details     Download: [pdf] (202.1kB )  


• Designing Reward Functions for Multiagent Systems: A Collective Intelligence Approach. K. Tumer and D. H. Wolpert. In ICML-2000 Workshop on Multiagent Learning: Theory and Practice, Stanford, CA, July 2000.
  Details     Download: (unavailable)


• Collective Intelligence for Optimization. D. H. Wolpert and K. Tumer. Pages 48-50 of collective article: ``Statistical Machine Learning for Large Scale Optimization'', J. Boyan, W. Buntine, and A. Jagota (Eds.), Neural Computing Surveys, 3:1–60, 2000.
  Details     Download: (unavailable)


• Collective Intelligence for Control of Distributed Dynamical Systems. D. H. Wolpert, K. Wheeler, and K. Tumer. Europhysics Letters, 49(6), March 2000.
  Details     Download: (unavailable)


• Illustration of the COIN Approach to the Design of Multiagent Systems. D. H. Wolpert and K. Tumer. In AGENTS-00/ECML-00 Workshop on Learning Agents, Barcelona, Spain, June 2000.
  Details     Download: (unavailable)


• Using Collective Intelligence to Route Internet Traffic. D. H. Wolpert, K. Tumer, and J. Frank. In Advances in Neural Information Processing Systems - 11, pp. 952–958, MIT Press, 1999.
  Details     Download: [pdf] (124.6kB )  


• Collective Intelligence. D. H. Wolpert and K. Tumer. In Fourth Workshop on Economics with Heterogeneous Interacting Agents, Genoa, Italy, June 1999.
  Details     Download: (unavailable)


• Collective Intelligence for Optimization. D. H. Wolpert and K. Tumer. In IJCAI-99 Workshop on Statistical Machine Learning for Large Scale Optimization, Stockholm, Sweden, July 1999.
  Details     Download: (unavailable)


• Collective Intelligence for Network Routing. D. Wolpert, K. Tumer, and A. M. Bell. In AAAI-99 Workshop, Orlando, FL, July 1999.
  Details     Download: (unavailable)

Multiagent Systems

• Ensemble Clustering with Voting Active Labels. A. K. Agogino and K. Tumer. Pattern Recognition Letters, 29(14):1947–1953, 2008.
  Details     Download: (unavailable)


• Analyzing and Visualizing Multiagent Rewards in Dynamic and Stochastic Environments. A. K. Agogino and K. Tumer. Journal of Autonomous Agents and Multi Agent Systems, 17(2):320–338, 2008.
  Details     Download: [pdf] (666.9kB )  


• Regulating Air Traffic Flow with Coupled Agents. A. Agogino and K. Tumer. In Proceedings of the Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal, May 2008.
  Details     Download: [pdf] (405.5kB )  


• A Multiagent Approach to Hyper-Redundant Manipulators. D. Hennes, K. Tumer, and K. Tuyls. In AAMAS-08 Workshop on Adaptive and Learning Agents, Estoril, Portugal, May 2008.
  Details     Download: (unavailable)


• Fast Multiagent Learning: Cashing in on Team Knowledge. N. Khani and K. Tumer. In Intelligent Engineering Systems through Artificial Neural Networks, pp. , ASME Press, 2008.
  Details     Download: (unavailable)


• Towards Coordinating Autonomous Robots for Exploration in Dynamic Environments. M. Knudson and K. Tumer. In Intelligent Engineering Systems through Artificial Neural Networks, pp. , ASME Press, 2008.
  Details     Download: (unavailable)


• Testing a Purportedly More Learnable Auction Mechanism. K. L. Milkman, J. Burns, D. C. Parkes, G. Barron, and K. Tumer. Applied Economics Research Bulletin, Special Issue (Auctions), 1:107–140, 2008.
  Details     Download: (unavailable)


• Traffic Congestion Management as a Learning Agent Coordination Problem. K. Tumer, A. K. Agogino, and Z. Welch. In A. Bazzan and F. Kluegl, editors, Multiagent Architectures for Traffic and Transportation Engineering, Lecture notes in AI, Springer, 2008. to appear
  Details     Download: (unavailable)


• Adaptive Management of Air Traffic Flow: A Multiagent Coordination Approach. K. Tumer and A. Agogino. In Proceedings of the Twenty Third AAAI Conference on Artificial Intelligence, Nectar Track, Chicago, IL, July 2008.
  Details     Download: [pdf] (244.2kB )  


• Aligning social welfare and agent preferences to alleviate traffic congestion. K. Tumer, Z. Welch, and A. Agogino. In Proceedings of the Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, Estoril, Portugal, May 2008.
  Details     Download: [pdf] (216.2kB )  


• Evolving Distributed Agents for Managing Air Traffic. A. Agogino and K. Tumer. In Proceedings of the Genetic and Evolutionary Computation Conference, London, UK, July 2007.
  Details     Download: (unavailable)


• Effective Policies for Resource Limited Agents. M. Knudson and K. Tumer. In AAMAS-07 Workshop on Adaptive and Learning Agents, Honolulu, HI, May 2007.
  Details     Download: (unavailable)


• Distributed Agent-Based Air Traffic Flow Management. K. Tumer and A. Agogino. In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 330–337, Honolulu,HI, May 2007. Best paper award
  Details     Download: [pdf] (544.3kB )  


• Handling Communication Restrictions and Team Formation in Congestion Games. A. K. Agogino and K. Tumer. Journal of Autonomous Agents and Multi Agent Systems, 13(1):97–115, 2006.
  Details     Download: [pdf] (349.8kB )  


• QUICR-Learning for Multiagent Coordination. A. Agogino and K. Tumer. In Proceedings of the 21st National Conference on Artificial Intelligence, Boston, MA, July 2006.
  Details     Download: [pdf] (157.5kB )  


• Distributed Evaluation Functions for Fault Tolerant Multi Rover Systems. A. Agogino and K. Tumer. In Proceedings of the Genetic and Evolutionary Computation Conference, Seattle, WA, July 2006.
  Details     Download: [pdf] (633.2kB )  


• Efficient Agent-Based Cluster Ensembles. A. Agogino and K. Tumer. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, Hakodate, Japan, May 2006.
  Details     Download: [pdf] (312.5kB )  


• Learning agents for distributed and robust spacecraft power management. S. Airiau, K. Tumer, and A. Agogino. In AAMAS-06 Workshop on Adaptation and Learning in Autonomous Agents and Multi Agent Systems, Hakodate, Japan, May 2006.
  Details     Download: (unavailable)


• Efficient Agent-Based Models for Non-Genomic Evolution. N. Gupta, A. Agogino, and K. Tumer. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, Hakodate, Japan, May 2006.
  Details     Download: [pdf] (239.2kB )  


• Efficient Reward Functions for Adaptive Multi-Rover Systems. K. Tumer and A. K. Agogino. In K. Tuyls, P. Jan't Hoen, S. Sen, and K. Verbeeck, editors, Learning and Adaptation in Multi Agent Systems, pp. 177–191, Lecture notes in AI, Springer, 2006.
  Details     Download: (unavailable)


• Coordinating Simple and Unreliable Agents. K. Tumer. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, Hakodate, Japan, May 2006. (short paper)
  Details     Download: (unavailable)


• Robust Coordination of a Large Set of Simple Rovers. K. Tumer and A. Agogino. In Proceedings of the IEEE Aerospace Conference, Big Sky, MO, March 2006.
  Details     Download: (unavailable)


• Agent Reward Shaping for Alleviating Traffic Congestion. K. Tumer and A. Agogino. In AAMAS-06 Workshop on Agents in Traffic and Transportation, Hakodate, Japan, May 2006.
  Details     Download: (unavailable)


• Multi Agent Reward Analysis for Learning in Noisy Domains. A. Agogino and K. Tumer. In Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Utrecht, Netherlands, July 2005.
  Details     Download: [pdf] (258.2kB )  


• Reinforcement Learning in Large Multi-agent Systems. A. Agogino and K. Tumer. In AAMAS-05 Workshop on Coordination of Large Scale Multiagent Systems, Utrecht, Netherlands, July 2005.
  Details     Download: [pdf] (186.4kB )  


• Designing Agent Utilities for Coordinated, Scalable and Robust Multiagent Systems. K. Tumer. In P. Scerri, R. Mailler, and R. Vincent , editors, Challenges in the Coordination of Large Scale Multiagent Systems, pp. 173–188, Springer, 2005.
  Details     Download: [pdf] (194.9kB )  


• Coordinating Multi-Rover Systems: Evaluation Functions for Dynamic and Noisy Environments. K. Tumer and A. Agogino. In The Genetic and Evolutionary Computation Conference, Washington, DC, June 2005.
  Details     Download: [pdf] (291.4kB )  


• Efficient Reward Functions for Adaptive Multi-Rover Systems. K. Tumer and A. Agogino. In AAMAS-05 Workshop on Learning and Adaptation in Multiagent Systems, Utrecht, Netherlands, July 2005.
  Details     Download: [pdf] (304.8kB )  


• Unifying Temporal and Structural Credit Assignment Problems. A. Agogino and K. Tumer. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, New York, NY, July 2004.
  Details     Download: [pdf] (239.9kB )  


• Providing Effective Access to Shared Resources: A COIN Approach. S. Airau, S. Sen, D. Wolpert, and K. Tumer. In G. Di Marzo Serugendo, A. Karageorgos, O. F. Rana, and F. Zambonelli, editors, Engineering Self-Organizing Systems: Nature-Inspired Approaches to Software Engineering, Lecture Notes in Computer Science, pp. 249–264, Springer-Verlag, 2004.
  Details     Download: [pdf] (208.5kB )  


• A Survey of Collectives. K. Tumer and D. Wolpert. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pp. 1–42, Springer, 2004.
  Details     Download: [pdf] (259.7kB )  


• Overcoming Communication Restrictions in Collectives. K. Tumer and A. Agogino. In Proceedings of the International Joint Conference on Neural Networks, Budapest, Hungary, July 2004.
  Details     Download: [pdf] (114.4kB )  


• Time-Extended Policies in Multiagent Reinforcement Learning. K. Tumer and A. Agogino. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1336–1337, New York, NY, July 2004.
  Details     Download: [pdf] (72.2kB )  


• Coordination in large Multiagent Systems. K. Tumer. In AAMAS-04 Workshop on Challenges in the Coordination of Large Scale Multiagent Systems, New York, NY, July 2004.
  Details     Download: (unavailable)


• Team Formation and Communication Restrictions in Collectives. A. Agogino and K. Tumer. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Australia, July 2003. (short paper)
  Details     Download: [pdf] (81.5kB )  


• Providing Effective Access to Shared Resources: A COIN Approach. S. Airau, S. Sen, D. Wolpert, and K. Tumer. In AAMAS-03 Workshop on Engineering Self-Organizing Systems, Melbourne, Australia, July 2003.
  Details     Download: (unavailable)


• Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers. K. Tumer and J. Lawson. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Australia, July 2003. (short paper)
  Details     Download: (unavailable)


• Learning Sequences of Actions in Collectives of Autonomous Agents. K. Tumer, A. Agogino, and D. Wolpert. In Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 378–385, Bologna, Italy, July 2002.
  Details     Download: [pdf] (241.8kB )  


• Collective Intelligence, Data Routing and Braess' Paradox. D. H. Wolpert and K. Tumer. Journal of Artificial Intelligence Research, 16:359–387, 2002.
  Details     Download: [pdf] (226.9kB )  


• Optimal Reward Functions in Distributed Reinforcement Learning. D. H. Wolpert and K. Tumer. In Proceedings of the Second Asia-Pacific Conference on Intelligent Agent Technology (IAT-2001), Maebashi City, Japan, October 2001.
  Details     Download: (unavailable)


• Reinforcement Learning in Distributed Domains: Beyond Team Games. D. H. Wolpert, J. Sill, and K. Tumer. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp. 819–824, Seattle, WA, 2001.
  Details     Download: [pdf] (257.3kB )  


• Collective Intelligence and Braess' Paradox. K. Tumer and D. H. Wolpert. In Proceedings of the Seventeenth National Conference on Artificial Intelligence, pp. 104–109, Austin, TX, 2000.
  Details     Download: [pdf] (202.1kB )  


• Designing Reward Functions for Multiagent Systems: A Collective Intelligence Approach. K. Tumer and D. H. Wolpert. In ICML-2000 Workshop on Multiagent Learning: Theory and Practice, Stanford, CA, July 2000.
  Details     Download: (unavailable)


• Adaptivity in Agent-Based Routing for Data Networks. D. H. Wolpert, S. Kirshner, C. J. Merz, and K. Tumer. In Proceedings of the fourth International Conference of Autonomous Agents, pp. 396–403, Barcelona, Spain, 2000.
  Details     Download: [pdf] (162.0kB )  


• Illustration of the COIN Approach to the Design of Multiagent Systems. D. H. Wolpert and K. Tumer. In AGENTS-00/ECML-00 Workshop on Learning Agents, Barcelona, Spain, June 2000.
  Details     Download: (unavailable)


• General Principles of Learning-Based Multiagent Systems. D. H. Wolpert, K. Wheeler, and K. Tumer. In Proceedings of the Third International Conference of Autonomous Agents, pp. 77–83, May 1999.
  Details     Download: [pdf] (237.9kB )  


• Using Collective Intelligence to Route Internet Traffic. D. H. Wolpert, K. Tumer, and J. Frank. In Advances in Neural Information Processing Systems - 11, pp. 952–958, MIT Press, 1999.
  Details     Download: [pdf] (124.6kB )  

Complex Systems

• Entropy Based Anomaly Detection Applied to Space Shuttle Main Engines. A. Agogino and K. Tumer. In Proceedings of the IEEE Aerospace Conference, Big Sky, MO, March 2006.
  Details     Download: [pdf] (1.6MB )  


• Complexity Signatures for System Health Monitoring. K. Tumer and A. Agogino. In Proceedings of the IEEE Aerospace Conference, Big Sky, MO, March 2005.
  Details     Download: [pdf] (330.8kB )  


• Collectives and the Design of Complex Systems, K. Tumer and D. Wolpert, editors. Springer, New York, 2004.
  Available from the publisher's website.
  ISBN 0-387-40165-2
  Details     Download: (unavailable)


• Coordination in Large Collectives. K. Tumer and D. Wolpert. In Y. Bar-Yam, editors, Fifth International Conference on Complex Systems, Perseus Books, 2004.
  Details     Download: (unavailable)


• Optimal Payoff Functions for Members of Collectives. D. H. Wolpert and K. Tumer. In F. Schweitzer, editors, Modeling Complexity in Economic and Social Systems, pp. 355–369, World Scientific, 2002.
  Details     Download: (unavailable)


• Beyond Mechanism Design. D. H. Wolpert and K. Tumer. In ICM Game Theory Conference, ``Heterogeneous and Social Games'' Special Session, Qingdao, China, August 2002.
  Details     Download: (unavailable)


• Optimal Payoff Functions for Members of Collectives. D. H. Wolpert and K. Tumer. Advances in Complex Systems, 4(2/3):265–279, 2001.
  Details     Download: [pdf] (276.5kB )  

Distributed Reinforcement Learning

• Analyzing and Visualizing Multiagent Rewards in Dynamic and Stochastic Environments. A. K. Agogino and K. Tumer. Journal of Autonomous Agents and Multi Agent Systems, 17(2):320–338, 2008.
  Details     Download: [pdf] (666.9kB )  


• Traffic Congestion Management as a Learning Agent Coordination Problem. K. Tumer, A. K. Agogino, and Z. Welch. In A. Bazzan and F. Kluegl, editors, Multiagent Architectures for Traffic and Transportation Engineering, Lecture notes in AI, Springer, 2008. to appear
  Details     Download: (unavailable)


• Distributed Agent-Based Air Traffic Flow Management. K. Tumer and A. Agogino. In Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 330–337, Honolulu,HI, May 2007. Best paper award
  Details     Download: [pdf] (544.3kB )  


• QUICR-Learning for Multiagent Coordination. A. Agogino and K. Tumer. In Proceedings of the 21st National Conference on Artificial Intelligence, Boston, MA, July 2006.
  Details     Download: [pdf] (157.5kB )  


• Efficient Reward Functions for Adaptive Multi-Rover Systems. K. Tumer and A. K. Agogino. In K. Tuyls, P. Jan't Hoen, S. Sen, and K. Verbeeck, editors, Learning and Adaptation in Multi Agent Systems, pp. 177–191, Lecture notes in AI, Springer, 2006.
  Details     Download: (unavailable)


• Multi Agent Reward Analysis for Learning in Noisy Domains. A. Agogino and K. Tumer. In Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Utrecht, Netherlands, July 2005.
  Details     Download: [pdf] (258.2kB )  


• Unifying Temporal and Structural Credit Assignment Problems. A. Agogino and K. Tumer. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, New York, NY, July 2004.
  Details     Download: [pdf] (239.9kB )  


• Time-Extended Policies in Multiagent Reinforcement Learning. K. Tumer and A. Agogino. In Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1336–1337, New York, NY, July 2004.
  Details     Download: [pdf] (72.2kB )  


• Learning Sequences of Actions in Collectives of Autonomous Agents. K. Tumer, A. Agogino, and D. Wolpert. In Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 378–385, Bologna, Italy, July 2002.
  Details     Download: [pdf] (241.8kB )  


• Optimal Reward Functions in Distributed Reinforcement Learning. D. H. Wolpert and K. Tumer. In Proceedings of the Second Asia-Pacific Conference on Intelligent Agent Technology (IAT-2001), Maebashi City, Japan, October 2001.
  Details     Download: (unavailable)


• Reinforcement Learning in Distributed Domains: Beyond Team Games. D. H. Wolpert, J. Sill, and K. Tumer. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp. 819–824, Seattle, WA, 2001.
  Details     Download: [pdf] (257.3kB )  


• Reinforcement Learning in Distributed Domains: An Inverse game Theoretic Approach. D. H. Wolpert and K. Tumer. In 2001 AAAI Spring Symposium on Game Theoretic and Decision Theoretic Agents, Stanford, CA, March 2001.
  Details     Download: (unavailable)


• General Principles of Learning-Based Multiagent Systems. D. H. Wolpert, K. Wheeler, and K. Tumer. In Proceedings of the Third International Conference of Autonomous Agents, pp. 77–83, May 1999.
  Details     Download: [pdf] (237.9kB )  

Intelligent Prognostics

• Entropy Based Anomaly Detection Applied to Space Shuttle Main Engines. A. Agogino and K. Tumer. In Proceedings of the IEEE Aerospace Conference, Big Sky, MO, March 2006.
  Details     Download: [pdf] (1.6MB )  


• Complexity Signatures for System Health Monitoring. K. Tumer and A. Agogino. In Proceedings of the IEEE Aerospace Conference, Big Sky, MO, March 2005.
  Details     Download: [pdf] (330.8kB )  


• A Distributed and Adaptive Health and Mission Management Architecture. K. Tumer, S. Uckun, and A. Agogino. In Integrated Systems Health Managemet Conference, Cincinati, OH, August 2005. extended abstract
  Details     Download: (unavailable)

Adaptive Routing

• Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers. K. Tumer and J. Lawson. In Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, Melbourne, Australia, July 2003. (short paper)
  Details     Download: (unavailable)


• Collective Intelligence, Data Routing and Braess' Paradox. D. H. Wolpert and K. Tumer. Journal of Artificial Intelligence Research, 16:359–387, 2002.
  Details     Download: [pdf] (226.9kB )  


• Collective Intelligence and Braess' Paradox. K. Tumer and D. H. Wolpert. In Proceedings of the Seventeenth National Conference on Artificial Intelligence, pp. 104–109, Austin, TX, 2000.
  Details     Download: [pdf] (202.1kB )  


• Adaptivity in Agent-Based Routing for Data Networks. D. H. Wolpert, S. Kirshner, C. J. Merz, and K. Tumer. In Proceedings of the fourth International Conference of Autonomous Agents, pp. 396–403, Barcelona, Spain, 2000.
  Details     Download: [pdf] (162.0kB )  


• Strategic Behavior, Learning and the Efficient Allocation of Network Resources. A. M. Bell, W. Sethares, D. Lucking-Reiley, D. H. Wolpert, K. Tumer, and J. Frank. In International Congress on Networks, Groups and Coalitions, Manresa, Spain, May 1999.
  Details     Download: (unavailable)


• Using Collective Intelligence to Route Internet Traffic. D. H. Wolpert, K. Tumer, and J. Frank. In Advances in Neural Information Processing Systems - 11, pp. 952–958, MIT Press, 1999.
  Details     Download: [pdf] (124.6kB )  


• Collective Intelligence for Network Routing. D. Wolpert, K. Tumer, and A. M. Bell. In AAAI-99 Workshop, Orlando, FL, July 1999.
  Details     Download: (unavailable)

Evolutionary Algorithms

• Efficient Evaluation Functions for Evolving Coordination. A. K. Agogino and K. Tumer. Evolutionary Computation, 16(2):257–288, 2008.
  Details     Download: (unavailable)


• Neuro-Evolutionary Navigation for Resource-Limited Mobile Robots . M. Knudson and K. Tumer. In Intelligent Engineering Systems through Artificial Neural Networks, pp. , ASME Press, 2008.
  Details     Download: (unavailable)


• A Neuro-evolutionary Approach to Micro Aerial Vehicle Control. M. Salichon and K. Tumer. In Intelligent Engineering Systems through Artificial Neural Networks, pp. , ASME Press, 2008.
  Details     Download: (unavailable)


• Evolving Distributed Agents for Managing Air Traffic. A. Agogino and K. Tumer. In Proceedings of the Genetic and Evolutionary Computation Conference, London, UK, July 2007.
  Details     Download: (unavailable)


• Coordinating Multi-Rover Systems: Evaluation Functions for Dynamic and Noisy Environments. K. Tumer and A. K. Agogino. In S. Yang, editors, Evolutionary Computation in Dynamic and Uncertain Environments, pp. 371–388, Springer, 2007.
  Details     Download: (unavailable)


• Distributed Evaluation Functions for Fault Tolerant Multi Rover Systems. A. Agogino and K. Tumer. In Proceedings of the Genetic and Evolutionary Computation Conference, Seattle, WA, July 2006.
  Details     Download: [pdf] (633.2kB )  


• Efficient Credit Assignment through Evaluation Function Decomposition. A. Agogino, K. Tumer, and R. Miikulainen. In The Genetic and Evolutionary Computation Conference, Washington, DC, June 2005.
  Details     Download: [pdf] (199.9kB )  


• Coordinating Multi-Rover Systems: Evaluation Functions for Dynamic and Noisy Environments. K. Tumer and A. Agogino. In The Genetic and Evolutionary Computation Conference, Washington, DC, June 2005.
  Details     Download: [pdf] (291.4kB )  


• Efficient Evaluation Functions for Multi-Rover Systems. A. Agogino and K. Tumer. In The Genetic and Evolutionary Computation Conference, pp. 1–12, Seatle, WA, June 2004.
  Details     Download: [pdf] (284.7kB )  


• Designing Genetic Algorithms for the State Assignment Problem. J. N. Amaral, K. Tumer, and J. Ghosh. IEEE Transactions on Systems, Man and Cybernetics, 25(4):687–695, April 1995.
  Details     Download: [pdf] (116.0kB )  


• Applying Genetic Algorithms to the State Assignment Problem: A case study. J. N. Amaral, J. Ghosh, and K. Tumer. In Adaptive and Learning Systems, Proceedings of the SPIE (Vol. 1706), pp. 2–13, Orlando, FL, April 1992.
  Details     Download: (unavailable)

Optimization

• Efficient Agent-Based Models for Non-Genomic Evolution. N. Gupta, A. Agogino, and K. Tumer. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, Hakodate, Japan, May 2006.
  Details     Download: [pdf] (239.2kB )  


• Efficient Credit Assignment through Evaluation Function Decomposition. A. Agogino, K. Tumer, and R. Miikulainen. In The Genetic and Evolutionary Computation Conference, Washington, DC, June 2005.
  Details     Download: [pdf] (199.9kB )  


• Improving Search Algorithms by Using Intelligent Coordinates. D. H. Wolpert, K. Tumer, and E. Bandari. Physical Review E, 69, 2004.
  Details     Download: [pdf] (107.0kB )  


• Collective Intelligence for Optimization. D. H. Wolpert and K. Tumer. Pages 48-50 of collective article: ``Statistical Machine Learning for Large Scale Optimization'', J. Boyan, W. Buntine, and A. Jagota (Eds.), Neural Computing Surveys, 3:1–60, 2000.
  Details     Download: (unavailable)


• Designing Genetic Algorithms for the State Assignment Problem. J. N. Amaral, K. Tumer, and J. Ghosh. IEEE Transactions on Systems, Man and Cybernetics, 25(4):687–695, April 1995.
  Details     Download: [pdf] (116.0kB )  


• Applying Genetic Algorithms to the State Assignment Problem: A case study. J. N. Amaral, J. Ghosh, and K. Tumer. In Adaptive and Learning Systems, Proceedings of the SPIE (Vol. 1706), pp. 2–13, Orlando, FL, April 1992.
  Details     Download: (unavailable)

Distributed Control

• Efficient Evaluation Functions for Evolving Coordination. A. K. Agogino and K. Tumer. Evolutionary Computation, 16(2):257–288, 2008.
  Details     Download: (unavailable)


• Coordinating Multi-Rover Systems: Evaluation Functions for Dynamic and Noisy Environments. K. Tumer and A. K. Agogino. In S. Yang, editors, Evolutionary Computation in Dynamic and Uncertain Environments, pp. 371–388, Springer, 2007.
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Economics/Game Theory

• Testing a Purportedly More Learnable Auction Mechanism. K. L. Milkman, J. Burns, D. C. Parkes, G. Barron, and K. Tumer. Applied Economics Research Bulletin, Special Issue (Auctions), 1:107–140, 2008.
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• Collectives and the Design of Complex Systems, K. Tumer and D. Wolpert, editors. Springer, New York, 2004.
  Available from the publisher's website.
  ISBN 0-387-40165-2
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• A Survey of Collectives. K. Tumer and D. Wolpert. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pp. 1–42, Springer, 2004.
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• Optimal Payoff Functions for Members of Collectives. D. H. Wolpert and K. Tumer. In F. Schweitzer, editors, Modeling Complexity in Economic and Social Systems, pp. 355–369, World Scientific, 2002.
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• Beyond Mechanism Design. D. H. Wolpert and K. Tumer. In ICM Game Theory Conference, ``Heterogeneous and Social Games'' Special Session, Qingdao, China, August 2002.
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• Reinforcement Learning in Distributed Domains: An Inverse game Theoretic Approach. D. H. Wolpert and K. Tumer. In 2001 AAAI Spring Symposium on Game Theoretic and Decision Theoretic Agents, Stanford, CA, March 2001.
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• Strategic Behavior, Learning and the Efficient Allocation of Network Resources. A. M. Bell, W. Sethares, D. Lucking-Reiley, D. H. Wolpert, K. Tumer, and J. Frank. In International Congress on Networks, Groups and Coalitions, Manresa, Spain, May 1999.
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• Collective Intelligence. D. H. Wolpert and K. Tumer. In Fourth Workshop on Economics with Heterogeneous Interacting Agents, Genoa, Italy, June 1999.
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Classifier Ensembles

• Ensemble Clustering with Voting Active Labels. A. K. Agogino and K. Tumer. Pattern Recognition Letters, 29(14):1947–1953, 2008.
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• Applications of Ensemble Methods (Guest Editorial). N. C. Oza and K. Tumer. Information Fusion, 9(1):2–3, 2008.
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• Classifier Ensembles: Select Real World Applications. N. C. Oza and K. Tumer. Information Fusion, 9(1):4–20, 2008.
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• Efficient Agent-Based Cluster Ensembles. A. Agogino and K. Tumer. In Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, Hakodate, Japan, May 2006.
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• Classification of Aircraft Maneuvers for Fault Detection. N. C. Oza, I. Y. Tumer, K. Tumer, and E. Huff. In Proceedings of the Fourth International Workshop on Multiple Classifier Systems, pp. 375–384, Springer, Surrey, UK, June 2003.
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• Bayes Error Rate Estimation using Classifier Ensembles. K. Tumer and J. Ghosh. International Journal of Smart Engineering System Design, 5(2):95–110, 2003.
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• Input Decimated Ensembles. K. Tumer and N. C. Oza. Pattern Analysis and Applications, 6(1):65–77, 2003.
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• Robust Combining of Disparate Classifiers through Order Statistics. K. Tumer and J. Ghosh. Pattern Analysis and Applications, 5(2):189–200, 2002.
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• Input Decimated Ensembles: Decorrelation through Dimensionality Reduction. N. C. Oza and K. Tumer. In Kittler, J. and Roli, F., editors, Proceedings of the Second International Workshop on Multiple Classifier Systems, pp. 238–249, Springer, Cambridge, UK, June 2001.
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• Ensemble Techniques for Data Mining in Heterogeneous Environments. J. Ghosh and K. Tumer. In Institute for Operations Research and the Management Sciences Conferences, San Antonio, TX, November 2000.
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• Robust Order Statistics Based Ensembles for Distributed Data Mining. K. Tumer and J. Ghosh. In H. Kargupta and P. Chan, editors, Advances in Distributed and Parallel Knowledge Discovery, pp. 185–210, AAAI/MIT Press, 2000.
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• Linear and Order Statistics Combiners for Pattern Classification. K. Tumer and J. Ghosh. In A. J. C. Sharkey, editors, Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems, pp. 127–162, Springer-Verlag, London, 1999.
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• Decimated Input Ensembles for Improved Generalization. K. Tumer and N. C. Oza. In Proceedings of the International Joint Conference on Neural Networks, Washington, D.C., July 1999.
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• Ensembles of Radial Basis Function Networks for Spectroscopic Detection of Cervical Pre-Cancer. K. Tumer, N. Ramanujam, J. Ghosh, and R. Richards-Kortum. IEEE Transactions on Biomedical Engineeiring, 45(8):953–961, 1998.
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• A Mutual Information Based Ensemble Method to Estimate the Bayes Error. K. Tumer, K. D. Bollacker, and J. Ghosh. In Intelligent Engineering Systems through Artificial Neural Networks, pp. 17–22, ASME Press, 1998.
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• Classifier Combining through Trimmed Means and Order Statistics. K. Tumer and J. Ghosh. In Proceedings of the International Joint Conference on Neural Networks, pp. 757–762, Anchorage, AL, June 1998.
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• Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks. K. Tumer, N. Ramanujam, R. Richards-Kortum, and J. Ghosh. In Advances in Neural Information Processing Systems - 9, pp. 981–987, M.I.T. Press, 1997.
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• Integration of Neural Classifiers for Passive Sonar Signals. J. Ghosh, K. Tumer, S. Beck, and L. Deuser. In C.T. Leondes, editors, Control and Dynamic Systems---Advances in Theory and Applications, pp. 301–338, Academic Press, 1996.
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• Analysis of Decision Boundaries in Linearly Combined Neural Classifiers. K. Tumer and J. Ghosh. Pattern Recognition, 29(2):341–348, 1996.
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• Error Correlation and Error Reduction in Ensemble Classifiers. K. Tumer and J. Ghosh. Connection Science, 8(3/4):385–404, 1996.
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• Estimating the Bayes Error Rate Through Classifier Combining. K. Tumer and J. Ghosh. In Proceedings of the Thirteenth International Conference on Pattern Recognition, pp. IV:695–99, Vienna, Austria, August 1996.
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• Classifier Combining: Analytical Results and Implications. K. Tumer and J. Ghosh. In Integrating Multiple Learned Models for Improving and Scaling Machine Learning Algorithms, workshop at the Thirteenth National Conference on Artificial Intelligence, Portland, OR, August 1996.
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• Linear and Order Statistics Combiners for Reliable Pattern Classification. K. Tumer. Ph.D. Thesis, The University of Texas, Austin, TX, 1996.
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• Order Statistics Combiners for Neural Classifiers. K. Tumer and J. Ghosh. In Proceedings of the World Congress on Neural Networks, pp. I:31–34, INNS Press, Washington D.C., July 1995.
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• Boundary Variance Reduction for Improved Classification through Hybrid Networks (Invited Paper). K. Tumer and J. Ghosh. In Applications and Science of Artificial Neural Networks, Proceedings of the SPIE (Vol. 2492), pp. 573–584, April 1995.
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• Structural Adaptation and Generalization in Supervised Feedforward Networks. J. Ghosh and K. Tumer. Journal of Artificial Neural Networks, 1(4):431–458, 1994.
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• A Framework for Estimating Performance Improvements in Hybrid Pattern Classifiers. K. Tumer and J. Ghosh. In Proceedings of the World Congress on Neural Networks, pp. III:220–225, INNS Press, San Diego, June 1994.
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• Integration of Local and Global Neural Classifiers for Passive Sonar Signals. J. Ghosh, K. Tumer, S. Beck, and L. Deuser. In Proceedings of the International Simulation Technology Conference, pp. 539–545, Houston, TX, November 1992.
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Bayes Error Estimation

• Bayes Error Rate Estimation using Classifier Ensembles. K. Tumer and J. Ghosh. International Journal of Smart Engineering System Design, 5(2):95–110, 2003.
  Details     Download: [pdf] (464.1kB )  


• A Mutual Information Based Ensemble Method to Estimate the Bayes Error. K. Tumer, K. D. Bollacker, and J. Ghosh. In Intelligent Engineering Systems through Artificial Neural Networks, pp. 17–22, ASME Press, 1998.
  Details     Download: (unavailable)


• Estimating the Bayes Error Rate Through Classifier Combining. K. Tumer and J. Ghosh. In Proceedings of the Thirteenth International Conference on Pattern Recognition, pp. IV:695–99, Vienna, Austria, August 1996.
  Details     Download: (unavailable)


• Classifier Combining: Analytical Results and Implications. K. Tumer and J. Ghosh. In Integrating Multiple Learned Models for Improving and Scaling Machine Learning Algorithms, workshop at the Thirteenth National Conference on Artificial Intelligence, Portland, OR, August 1996.
  Details     Download: (unavailable)


• Linear and Order Statistics Combiners for Reliable Pattern Classification. K. Tumer. Ph.D. Thesis, The University of Texas, Austin, TX, 1996.
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• Limits to Performance Gains in Combined Neural Classifiers. K. Tumer and J. Ghosh. In Intelligent Engineering Systems through Artificial Neural Networks, pp. 419–424, St. Louis, November 1995.
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Other Topics

• Optimization of Sensor/Neuro-Controller Pairings for Effective Navigation. J. Junell, M. Knudson, and K. Tumer. In Intelligent Engineering Systems through Artificial Neural Networks, pp. , ASME Press, 2008.
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• Structural Adaptation and Generalization in Supervised Feedforward Networks. J. Ghosh and K. Tumer. Journal of Artificial Neural Networks, 1(4):431–458, 1994.
  Details     Download: (unavailable)


• Sequence Recognition by Input Anticipation. K. Tumer and J. Ghosh. In Proceedings of the Seventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Austin, TX, June 1994.
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• Structural Adaptation and Generalization in Neural Networks. K. Tumer. Master's Thesis, The University of Texas, Austin, TX,1992.
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• A New Algorithm for Automatic Shoulder Bed Correction. K. Tumer, D. Torres, and R. Chemali. In Transactions of the Society of Professional Well Log Analysts' 32nd Annual Logging Symposium, SPWLA, Midland, TX, June 1991.
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