2024

  1. Reinforcing Inter-Class Dependencies in the Asymmetric Island Model
    A. Festa, G. Dixit, and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, Australia, July 14-18, 2024

  2. Informed Diversity Search for Learning in Asymmetric Multiagent Systems
    G. Dixit and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, Australia, July 14-18, 2024

  3. Influence Based Fitness Shaping for Coevolutionary Agents
    E. Gonzalez, S. Viswanathan, and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, Australia, July 14-18, 2024

  4. Learning Aligned Local Evaluations For Better Credit Assignment In Cooperative Coevolution
    J. Cook and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2024, Melbourne, Australia, July 14-18, 2024

  5. Redefining the Behavior Space for Multi-Objective MAP-Elites (Extended Abstract)
    A. Nickelson and K. Tumer
    Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2024, Companion Volume, Melbourne, Australia, July 14-18, 2024

  6. Multidimensional Archive Of The State Space (Extended Abstract)
    J. Cook and K. Tumer
    Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2024, Companion Volume, Melbourne, Australia, July 14-18, 2024

  7. Influence-Focused Asymmetric Island Model (Extended Abstract)
    A. Festa, G. Dixit, and K. Tumer
    Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024, Auckland, New Zealand, 06 May 2024 - 10 May 2024 [ bibtex ] [ pdf ]

  8. Entropy Seeking Constrained Multiagent Reinforcement Learning (Extended Abstract)
    A. Aydeniz, E. Marchesini, C. Amato, and K. Tumer
    Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024, Auckland, New Zealand, 06 May 2024 - 10 May 2024 [ bibtex ] [ pdf ]

  9. Indirect Credit Assignment in a Multiagent System (Extended Abstract)
    E. Gonzalez, S. Viswanathan, and K. Tumer
    Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024, Auckland, New Zealand, 06 May 2024 - 10 May 2024 [ bibtex ] [ pdf ]

2023

  1. Learning Inter-Agent Synergies in Asymmetric Multiagent Systems
    G. Dixit and K. Tumer
    Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023, London, United Kingdom, 29 May 2023 - 2 June 2023 [ bibtex ] [ pdf ]

  2. Multi-Team Fitness Critics For Robust Teaming
    J. Cook, T. Scheiner, and K. Tumer
    Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023, London, United Kingdom, 29 May 2023 - 2 June 2023 [ bibtex ] [ pdf ]

  3. Knowledge Injection for Multiagent Systems via Counterfactual Perception Shaping
    N. Zerbel and K. Tumer
    ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023) [ bibtex ] [ pdf ]

  4. Knowledge Shaped Behavior Generation for Online Adaptation
    C. Yates and K. Tumer
    Companion Proceedings of the Conference on Genetic and Evolutionary Computation, GECCO 2023, Companion Volume, Lisbon, Portugal, July 15-19, 2023 [ bibtex ] [ pdf ]

  5. Novelty Seeking Multiagent Evolutionary Reinforcement Learning
    A. Aydeniz, R. Loftin, and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 [ bibtex ] [ pdf ]

  6. Leveraging Fitness Critics To Learn Robust Teamwork
    J. Cook, K. Tumer, and T. Scheiner
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 [ bibtex ] [ pdf ]

  7. Learning Synergies for Multi-Objective Optimization in Asymmetric Multiagent Systems
    G. Dixit and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2023, Lisbon, Portugal, July 15-19, 2023 [ bibtex ] [ pdf ]

  8. Contextual Multi-Objective Path Planning
    A. Nickelson, K. Tumer, and W. Smart
    IEEE International Conference on Robotics and Automation, ICRA 2023, London, UK, May 29 - June 2, 2023 [ bibtex ] [ pdf ]

  9. Shaping the Behavior Space with Counterfactual Agents in Multi-Objective Map Elites
    A. Nickelson, N. Zerbel, G. Dixit, and K. Tumer
    Proceedings of the 15th International Joint Conference on Computational Intelligence, IJCCI 2023, Rome, Italy, November 13-15, 2023 [ bibtex ] [ pdf ]

  10. Entropy Maximization in High Dimensional Multiagent State Spaces
    A. Aydeniz, E. Marchesini, R. Loftin, and K. Tumer
    International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2023, Boston, MA, USA, December 4-5, 2023 [ bibtex ] [ pdf ]

2022

  1. Behavior Exploration and Team Balancing for Heterogeneous Multiagent Coordination
    G. Dixit and K. Tumer
    21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022, Auckland, New Zealand, May 9-13, 2022 [ bibtex ] [ pdf ]

  2. Entropy-based local fitnesses for evolutionary multiagent systems
    A. Aydeniz, A. Nickelson, and K. Tumer
    GECCO ’22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 [ bibtex ] [ pdf ]

  3. Balancing teams with quality-diversity for heterogeneous multiagent coordination
    G. Dixit and K. Tumer
    GECCO ’22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 [ bibtex ] [ pdf ]

  4. Bootstrapped fitness critics with bidirectional temporal difference
    G. Rockefeller and K. Tumer
    GECCO ’22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9 - 13, 2022 [ bibtex ] [ pdf ]

  5. Fitness shaping for multiple teams
    J. Cook and K. Tumer
    GECCO ’22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9 - 13, 2022 [ bibtex ] [ pdf ]

  6. Diversifying behaviors for learning in asymmetric multiagent systems
    G. Dixit, E. Gonzalez, and K. Tumer
    GECCO ’22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9 - 13, 2022 [ bibtex ] [ pdf ]

2021

  1. Dynamic Skill Selection for Learning Joint Actions
    E. Sachdeva, S. Khadka, S. Majumdar, and K. Tumer
    AAMAS ’21: 20th International Conference on Autonomous Agents and Multiagent Systems, Virtual Event, United Kingdom, May 3-7, 2021 [ bibtex ] [ pdf ]

  2. Ad hoc teaming through evolution
    J. Cook and K. Tumer
    GECCO ’21: Genetic and Evolutionary Computation Conference, Companion Volume, Lille, France, July 10-14, 2021 [ bibtex ] [ pdf ]

  3. Heterogeneous agent coordination via adaptive quality diversity and specialization
    G. Dixit, C. Koll, and K. Tumer
    GECCO ’21: Genetic and Evolutionary Computation Conference, Companion Volume, Lille, France, July 10-14, 2021 [ bibtex ] [ pdf ]

  4. MAEDyS: multiagent evolution via dynamic skill selection
    E. Sachdeva, S. Khadka, S. Majumdar, and K. Tumer
    GECCO ’21: Genetic and Evolutionary Computation Conference, Lille, France, July 10-14, 2021 [ bibtex ] [ pdf ]

  5. Adaptive multi-fitness learning for robust coordination
    C. Yates, A. Aydeniz, and K. Tumer
    GECCO ’21: Genetic and Evolutionary Computation Conference, Companion Volume, Lille, France, July 10-14, 2021 [ bibtex ] [ pdf ]

  6. Reactive Multi-Fitness Learning for Robust Multiagent Teaming
    C. Yates, A. Aydeniz, and K. Tumer
    International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2021, Cambridge, United Kingdom, November 4-5, 2021 [ bibtex ] [ pdf ]

2020

  1. The impact of agent definitions and interactions on multiagent learning for coordination in traffic management domains
    J. Chung, D. Miklic, L. Sabattini, K. Tumer, and R. Siegwart
    Journal: Auton. Agents Multi Agent Syst. [ bibtex ] [ pdf ]

  2. Gaussian Processes as Multiagent Reward Models
    G. Dixit, S. Airiau, and K. Tumer
    Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS ’20, Auckland, New Zealand, May 9-13, 2020 [ bibtex ] [ pdf ]

  3. Multi-level Fitness Critics for Cooperative Coevolution
    G. Rockefeller, S. Khadka, and K. Tumer
    Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS ’20, Auckland, New Zealand, May 9-13, 2020 [ bibtex ] [ pdf ]

  4. The Power of Suggestion
    N. Zerbel and K. Tumer
    Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS ’20, Auckland, New Zealand, May 9-13, 2020 [ bibtex ] [ pdf ]

  5. Multi-fitness learning for behavior-driven cooperation
    C. Yates, R. Christopher, and K. Tumer
    GECCO ’20: Genetic and Evolutionary Computation Conference, Cancún Mexico, July 8-12, 2020 [ bibtex ] [ pdf ]

  6. Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
    S. Majumdar, S. Khadka, S. Miret, S. McAleer, and K. Tumer
    Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event [ bibtex ] [ pdf ]

2019

  1. Modeling multidisciplinary design with multiagent learning
    D. Hulse, K. Tumer, C. Hoyle, and I. Tumer
    Journal: Artif. Intell. Eng. Des. Anal. Manuf. [ bibtex ] [ pdf ]

  2. A multiagent framework for learning dynamic traffic management strategies
    J. Chung, C. Rebhuhn, C. Yates, G. Hollinger, and K. Tumer
    Journal: Auton. Robots [ bibtex ] [ pdf ]

  3. Neuroevolution of a Modular Memory-Augmented Neural Network for Deep Memory Problems
    S. Khadka, J. Chung, and K. Tumer
    Journal: Evol. Comput. [ bibtex ] [ pdf ]

  4. The Impact of Agent Definitions and Interactions on Multiagent Learning for Coordination
    J. Chung, D. Miklic, L. Sabattini, K. Tumer, and R. Siegwart
    Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, Montreal, QC, Canada, May 13-17, 2019 [ bibtex ] [ pdf ]

  5. Memory based Multiagent One Shot Learning
    S. Khadka, C. Yates, and K. Tumer
    Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, Montreal, QC, Canada, May 13-17, 2019 [ bibtex ] [ pdf ]

  6. Curriculum Learning for Tightly Coupled Multiagent Systems
    G. Rockefeller, P. Mannion, and K. Tumer
    Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS ’19, Montreal, QC, Canada, May 13-17, 2019 [ bibtex ] [ pdf ]

  7. Collaborative Evolutionary Reinforcement Learning
    S. Khadka, S. Majumdar, T. Nassar, Z. Dwiel, E. Tumer, S. Miret, Y. Liu, and K. Tumer
    Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA [ bibtex ] [ pdf ]

  8. Memory-Based Multiagent One-Shot Learning: Extended Abstract
    S. Khadka, C. Yates, and K. Tumer
    2019 International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019, New Brunswick, NJ, USA, August 22-23, 2019 [ bibtex ] [ pdf ]

  9. Dirichlet-Multinomial Counterfactual Rewards for Heterogeneous Multiagent Systems
    G. Dixit, N. Zerbel, and K. Tumer
    2019 International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019, New Brunswick, NJ, USA, August 22-23, 2019 [ bibtex ] [ pdf ]

  10. Fitness Critics for Multiagent Learning: Extended Abstract
    G. Rockefeller, P. Mannion, and K. Tumer
    2019 International Symposium on Multi-Robot and Multi-Agent Systems, MRS 2019, New Brunswick, NJ, USA, August 22-23, 2019 [ bibtex ] [ pdf ]

  11. Collaborative Evolutionary Reinforcement Learning
    S. Khadka, S. Majumdar, T. Nassar, Z. Dwiel, E. Tumer, S. Miret, Y. Liu, and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

  12. Evolutionary Reinforcement Learning for Sample-Efficient Multiagent Coordination
    S. Khadka, S. Majumdar, and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

2018

  1. Design of Complex Engineered Systems Using Multi-Agent Coordination
    N. Zurita, M. Colby, I. Tumer, C. Hoyle, and K. Tumer
    Journal: J. Comput. Inf. Sci. Eng. [ bibtex ] [ pdf ]

  2. When Less is More: Reducing Agent Noise with Probabilistically Learning Agents
    J. Chung, S. Chow, and K. Tumer
    Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2018, Stockholm, Sweden, July 10-15, 2018 [ bibtex ] [ pdf ]

  3. A Memory-based Multiagent Framework for Adaptive Decision Making
    S. Khadka, C. Yates, and K. Tumer
    Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2018, Stockholm, Sweden, July 10-15, 2018 [ bibtex ] [ pdf ]

  4. Evolution-Guided Policy Gradient in Reinforcement Learning
    S. Khadka and K. Tumer
    Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada [ bibtex ] [ pdf ]

  5. Evolutionary Reinforcement Learning
    S. Khadka and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

2017

  1. Fitness function shaping in multiagent cooperative coevolutionary algorithms
    M. Colby and K. Tumer
    Journal: Auton. Agents Multi Agent Syst. [ bibtex ] [ pdf ]

  2. Evolving memory-augmented neural architecture for deep memory problems
    S. Khadka, J. Chung, and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2017, Berlin, Germany, July 15-19, 2017 [ bibtex ] [ pdf ]

  3. Memory-augmented multi-robot teams that learn to adapt
    S. Khadka, J. Chung, and K. Tumer
    2017 International Symposium on Multi-Robot and Multi-Agent Systems (MRS), Los Angeles, CA, USA, December 4-5, 2017 [ bibtex ] [ pdf ]

  4. Soft snake robots: Mechanical design and geometric gait implementation
    C. Branyan, C. Fleming, J. Remaley, A. Kothari, K. Tumer, R. Hatton, and Y. Mengüç
    2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017, Macau, China, December 5-8, 2017 [ bibtex ] [ pdf ]

2016

  1. Autonomous Multiagent Space Exploration with High-Level Human Feedback
    M. Colby, L. Yliniemi, and K. Tumer
    Journal: J. Aerosp. Inf. Syst. [ bibtex ] [ pdf ]

  2. Combining reward shaping and hierarchies for scaling to large multiagent systems
    C. HolmesParker, A. Agogino, and K. Tumer
    Journal: Knowl. Eng. Rev. [ bibtex ] [ pdf ]

  3. Multi-objective multiagent credit assignment in reinforcement learning and NSGA-II
    L. Yliniemi and K. Tumer
    Journal: Soft Comput. [ bibtex ] [ pdf ]

  4. Using Awareness to Promote Richer, More Human-Like Behaviors in Artificial Agents
    L. Yliniemi and K. Tumer
    Autonomous Agents and Multiagent Systems - AAMAS 2016 Workshops, - Visionary Papers - , Singapore, Singapore, May 9-10, 2016, Revised Selected Papers [ bibtex ] [ pdf ]

  5. Local Approximation of Difference Evaluation Functions
    M. Colby, T. Duchow-Pressley, J. Chung, and K. Tumer
    Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, Singapore, May 9-13, 2016 [ bibtex ] [ pdf ]

  6. Multiobjective Neuroevolutionary Control for a Fuel Cell Turbine Hybrid Energy System
    M. Colby, L. Yliniemi, P. Pezzini, D. Tucker, K. Bryden, and K. Tumer
    Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20 - 24, 2016 [ bibtex ] [ pdf ]

  7. Neuroevolution of a Hybrid Power Plant Simulator
    S. Khadka, K. Tumer, M. Colby, D. Tucker, P. Pezzini, and K. Bryden
    Proceedings of the 2016 on Genetic and Evolutionary Computation Conference, Denver, CO, USA, July 20 - 24, 2016 [ bibtex ] [ pdf ]

  8. D++: Structural credit assignment in tightly coupled multiagent domains
    A. Rahmattalabi, J. Chung, M. Colby, and K. Tumer
    2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016, Daejeon, South Korea, October 9-14, 2016 [ bibtex ] [ pdf ]

2015

  1. Learning Tensegrity Locomotion Using Open-Loop Control Signals and Coevolutionary Algorithms
    A. Iscen, K. Caluwaerts, J. Bruce, A. Agogino, V. SunSpiral, and K. Tumer
    Journal: Artif. Life [ bibtex ] [ pdf ]

  2. Simulation of the introduction of new technologies in air traffic management
    L. Yliniemi, A. Agogino, and K. Tumer
    Journal: Connect. Sci. [ bibtex ] [ pdf ]

  3. Counterfactual Exploration for Improving Multiagent Learning
    M. Colby, S. Kharaghani, C. HolmesParker, and K. Tumer
    Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, May 4-8, 2015 [ bibtex ] [ pdf ]

  4. Multi-Objective Multiagent Credit Assignment in NSGA-II Using Difference Evaluations
    L. Yliniemi, D. Wilson, and K. Tumer
    Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, May 4-8, 2015 [ bibtex ] [ pdf ]

  5. Approximating Difference Evaluations with Local Information
    M. Colby, W. Curran, and K. Tumer
    Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, May 4-8, 2015 [ bibtex ] [ pdf ]

  6. A Replicator Dynamics Analysis of Difference Evaluation Functions
    M. Colby and K. Tumer
    Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015, Istanbul, Turkey, May 4-8, 2015 [ bibtex ] [ pdf ]

  7. An Evolutionary Game Theoretic Analysis of Difference Evaluation Functions
    M. Colby and K. Tumer
    Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015 [ bibtex ] [ pdf ]

  8. Learning Based Control of a Fuel Cell Turbine Hybrid Power System
    A. Gabler, M. Colby, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015, Companion Material Proceedings [ bibtex ] [ pdf ]

  9. Complete Multi-Objective Coverage with PaCcET
    L. Yliniemi and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, July 11-15, 2015, Companion Material Proceedings [ bibtex ] [ pdf ]

  10. Learning to trick cost-based planners into cooperative behavior
    C. Rebhuhn, R. Skeele, J. Chung, G. Hollinger, and K. Tumer
    2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015, Hamburg, Germany, September 28 - October 2, 2015 [ bibtex ] [ pdf ]

  11. Implicit adaptive multi-robot coordination in dynamic environments
    M. Colby, J. Chung, and K. Tumer
    2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015, Hamburg, Germany, September 28 - October 2, 2015 [ bibtex ] [ pdf ]

2014

  1. Multirobot Coordination for Space Exploration
    L. Yliniemi, A. Agogino, and K. Tumer
    Journal: AI Mag. [ bibtex ] [ pdf ]

  2. Multiagent Flight Control in Dynamic Environments with Cooperative Coevolutionary Algorithms
    M. Colby, M. Knudson, and K. Tumer
    2014 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 24-26, 2014 [ bibtex ] [ pdf ]

  3. Announced Strategy Types in Multiagent RL for Conflict-Avoidance in the National Airspace
    C. Rebhuhn, M. Knudson, and K. Tumer
    2014 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 24-26, 2014 [ bibtex ] [ pdf ]

  4. Potential-based difference rewards for multiagent reinforcement learning
    S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France, May 5-9, 2014 [ bibtex ] [ pdf ]

  5. CLEANing the reward: counterfactual actions to remove exploratory action noise in multiagent learning (extended abstract)
    C. HolmesParker, M. Taylor, A. Agogino, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France, May 5-9, 2014 [ bibtex ] [ pdf ]

  6. Using reward/utility based impact scores in partitioning
    W. Curran, A. Agogino, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France, May 5-9, 2014 [ bibtex ] [ pdf ]

  7. Approximating difference evaluations with local knowledge
    M. Colby, W. Curran, C. Rebhuhn, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’14, Paris, France, May 5-9, 2014 [ bibtex ] [ pdf ]

  8. Hierarchical simulation for complex domains: air traffic flow management
    W. Curran, A. Agogino, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’14, Vancouver, BC, Canada, July 12-16, 2014 [ bibtex ] [ pdf ]

  9. Evolutionary agent-based simulation of the introduction of new technologies in air traffic management
    L. Yliniemi, A. Agogino, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’14, Vancouver, BC, Canada, July 12-16, 2014 [ bibtex ] [ pdf ]

  10. Flop and roll: Learning robust goal-directed locomotion for a Tensegrity Robot
    A. Iscen, A. Agogino, V. SunSpiral, and K. Tumer
    2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014, Chicago, IL, USA, September 14-18, 2014 [ bibtex ] [ pdf ]

  11. PaCcET: An Objective Space Transformation to Iteratively Convexify the Pareto Front
    L. Yliniemi and K. Tumer
    Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings [ bibtex ] [ pdf ]

  12. Multi-objective Multiagent Credit Assignment Through Difference Rewards in Reinforcement Learning
    L. Yliniemi and K. Tumer
    Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings [ bibtex ] [ pdf ]

  13. CLEAN Rewards to Improve Coordination by Removing Exploratory Action Noise
    C. HolmesParker, M. Taylor, A. Agogino, and K. Tumer
    2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014 - Volume III [ bibtex ] [ pdf ]

2013

  1. Coordinating actions in congestion games: impact of top-down and bottom-up utilities
    K. Tumer and S. Proper
    Journal: Auton. Agents Multi Agent Syst. [ bibtex ] [ pdf ]

  2. Dynamic Partnership Formation for Multi-Rover Coordination
    M. Knudson and K. Tumer
    Journal: Adv. Complex Syst. [ bibtex ] [ pdf ]

  3. Robust predictive cruise control for commercial vehicles
    J. Junell and K. Tumer
    Journal: Int. J. Gen. Syst. [ bibtex ] [ pdf ]

  4. A neuro-evolutionary approach to control surface segmentation for micro aerial vehicles
    M. Salichon and K. Tumer
    Journal: Int. J. Gen. Syst. [ bibtex ] [ pdf ]

  5. Efficient Objective Functions for Coordinated Learning in Large-Scale Distributed OSA Systems
    M. NoroozOliaee, B. Hamdaoui, and K. Tumer
    Journal: IEEE Trans. Mob. Comput. [ bibtex ] [ pdf ]

  6. Multiagent Learning with a Noisy Global Reward Signal
    S. Proper and K. Tumer
    Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, July 14-18, 2013, Bellevue, Washington, USA [ bibtex ] [ pdf ]

  7. Elo Ratings for Structural Credit Assignment in Multiagent Systems
    L. Yliniemi and K. Tumer
    Late-Breaking Developments in the Field of Artificial Intelligence, Bellevue, Washington, USA, July 14-18, 2013 [ bibtex ] [ pdf ]

  8. Multiagent reinforcement learning in a distributed sensor network with indirect feedback
    M. Colby and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  9. CLEAN rewards for improving multiagent coordination in the presence of exploration
    C. HolmesParker, A. Agogino, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  10. Exploiting structure and utilizing agent-centric rewards to promote coordination in large multiagent systems
    C. HolmesParker, A. Agogino, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  11. Learning to control complex tensegrity robots
    A. Iscen, A. Agogino, V. SunSpiral, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  12. Decentralized coordination via task decomposition and reward shaping
    A. Iscen and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  13. Graphical models in continuous domains for multiagent reinforcement learning
    S. Proper and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  14. Addressing hard constraints in the air traffic problem through partitioning and difference rewards
    W. Curran, A. Agogino, and K. Tumer
    International conference on Autonomous Agents and Multi-Agent Systems, AAMAS ’13, Saint Paul, MN, USA, May 6-10, 2013 [ bibtex ] [ pdf ]

  15. Partitioning agents and shaping their evaluation functions in air traffic problems with hard constraints
    W. Curran, A. Agogino, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’13, Amsterdam, The Netherlands, July 6-10, 2013, Companion Material Proceedings [ bibtex ] [ pdf ]

  16. Controlling tensegrity robots through evolution
    A. Iscen, A. Agogino, V. SunSpiral, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’13, Amsterdam, The Netherlands, July 6-10, 2013 [ bibtex ] [ pdf ]

2012

  1. A multiagent approach to managing air traffic flow
    A. Agogino and K. Tumer
    Journal: Auton. Agents Multi Agent Syst. [ bibtex ] [ pdf ]

  2. Ten Years of AAMAS: Introduction to the Special Issue
    L. Sonenberg, P. Stone, K. Tumer, and P. Yolum
    Journal: AI Mag. [ bibtex ] [ pdf ]

  3. Combining coordination mechanisms to improve performance in multi-robot teams
    E. Nasroullahi and K. Tumer
    Journal: Artif. Intell. Res. [ bibtex ] [ pdf ]

  4. Coordinating Secondary-User Behaviors for Inelastic Traffic Reward Maximization in Large-Scale }osa Networks
    B. Hamdaoui, M. NoroozOliaee, K. Tumer, and A. Rayes
    Journal: IEEE Trans. Netw. Serv. Manag. [ bibtex ] [ pdf ]

  5. Evolving a Multiagent Controller for Micro Aerial Vehicles
    M. Salichon and K. Tumer
    Journal: IEEE Trans. Syst. Man Cybern. Part C [ bibtex ] [ pdf ]

  6. Shaping fitness functions for coevolving cooperative multiagent systems
    M. Colby and K. Tumer
    International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, Valencia, Spain, June 4-8, 2012 (3 Volumes) [ bibtex ] [ pdf ]

  7. Modeling difference rewards for multiagent learning
    S. Proper and K. Tumer
    International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, Valencia, Spain, June 4-8, 2012 (3 Volumes) [ bibtex ] [ pdf ]

  8. Evolving distributed resource sharing for cubesat constellations
    A. Agogino, C. HolmesParker, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’12, Philadelphia, PA, USA, July 7-11, 2012 [ bibtex ] [ pdf ]

  9. Evolving large scale UAV communication system
    A. Agogino, C. HolmesParker, and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’12, Philadelphia, PA, USA, July 7-11, 2012 [ bibtex ] [ pdf ]

  10. Policy transfer in mobile robots using neuro-evolutionary navigation
    M. Knudson and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO ’12, Philadelphia, PA, USA, July 7-11, 2012, Companion Material Proceedings [ bibtex ] [ pdf ]

2011

  1. Adaptive navigation for autonomous robots
    M. Knudson and K. Tumer
    Journal: Robotics Auton. Syst. [ bibtex ] [ pdf ]

  2. Agent fitness functions for evolving coordinated sensor networks
    C. Roth, M. Knudson, and K. Tumer
    13th Annual Genetic and Evolutionary Computation Conference, GECCO 2011, Proceedings, Dublin, Ireland, July 12-16, 2011 [ bibtex ] [ pdf ]

  3. Optimizing ballast design of wave energy converters using evolutionary algorithms
    M. Colby, E. Nasroullahi, and K. Tumer
    13th Annual Genetic and Evolutionary Computation Conference, GECCO 2011, Proceedings, Dublin, Ireland, July 12-16, 2011 [ bibtex ] [ pdf ]

  4. Aligning Spectrum-User Objectives for Maximum Inelastic-Traffic Reward
    B. Hamdaoui, M. NoroozOliaee, K. Tumer, and A. Rayes
    Proceedings of 20th International Conference on Computer Communications and Networks, ICCCN 2011, Maui, Hawaii, USA, July 31 - August 4, 2011 [ bibtex ] [ pdf ]

  5. Achieving optimal elastic traffic rewards in dynamic multichannel access
    M. NoroozOliaee, B. Hamdaoui, and K. Tumer
    2011 International Conference on High Performance Computing & Simulation, HPCS 2012, Istanbul, Turkey, July 4-8, 2011 [ bibtex ] [ pdf ]

  6. 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Taipei, Taiwan, May 2-6, 2011, Volume 1-3
    L. Sonenberg, P. Stone, K. Tumer, and P. Yolum
    10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), Taipei, Taiwan, May 2-6, 2011, Volume 1-3

  7. Collective Intelligence, Data Routing and Braess’ Paradox
    K. Tumer and D. Wolpert
    Journal: CoRR [ bibtex ] [ pdf ]

2010

  1. A Multiagent Coordination Approach to Robust Consensus Clustering
    A. Agogino and K. Tumer
    Journal: Adv. Complex Syst. [ bibtex ] [ pdf ]

  2. Robot coordination with ad-hoc team formation
    M. Knudson and K. Tumer
    9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), Toronto, Canada, May 10-14, 2010, Volume 1-3 [ bibtex ] [ pdf ]

  3. Coevolution of heterogeneous multi-robot teams
    M. Knudson and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2010, Proceedings, Portland, Oregon, USA, July 7-11, 2010 [ bibtex ] [ pdf ]

  4. A neuro-evolutionary approach to micro aerial vehicle control
    M. Salichon and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2010, Proceedings, Portland, Oregon, USA, July 7-11, 2010 [ bibtex ] [ pdf ]

  5. Robust neuro-control for a micro quadrotor
    J. III and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2010, Proceedings, Portland, Oregon, USA, July 7-11, 2010 [ bibtex ] [ pdf ]

2009

  1. Learning from Actions not Taken in Multiagent Systems
    K. Tumer and N. Khani
    Journal: Adv. Complex Syst. [ bibtex ] [ pdf ]

  2. Multiagent Learning for Black Box System Reward Functions
    K. Tumer and A. Agogino
    Journal: Adv. Complex Syst. [ bibtex ] [ pdf ]

  3. Learning Indirect Actions in Complex Domains: Action Suggestions for Air Traffic Control
    A. Agogino and K. Tumer
    Journal: Adv. Complex Syst. [ bibtex ] [ pdf ]

  4. Improving Air Traffic Management with a Learning Multiagent System
    K. Tumer and A. Agogino
    Journal: IEEE Intell. Syst. [ bibtex ] [ pdf ]

  5. Coordinating Learning Agents for Multiple Resource Job Scheduling
    K. Tumer and J. Lawson
    Adaptive and Learning Agents, Second Workshop, ALA 2009, Held as Part of the AAMAS 2009 Conference in Budapest, Hungary, May 12, 2009, Revised Selected Papers [ bibtex ] [ pdf ]

  6. Improving air traffic management through agent suggestions
    A. Agogino and K. Tumer
    8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), Budapest, Hungary, May 10-15, 2009, Volume 2 [ bibtex ] [ pdf ]

  7. Learning from actions not taken: a multiagent learning algorithm
    N. Khani and K. Tumer
    8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2009), Budapest, Hungary, May 10-15, 2009, Volume 2 [ bibtex ] [ pdf ]

  8. Traffic Congestion Management as a Learning Agent Coordination Problem
    K. Tumer, Z. Welch, and A. Agogino
    Multi-Agent Systems for Traffic and Transportation Engineering [ bibtex ] [ pdf ]

2008

  1. Analyzing and visualizing multiagent rewards in dynamic and stochastic domains
    A. Agogino and K. Tumer
    Journal: Auton. Agents Multi Agent Syst. [ bibtex ] [ pdf ]

  2. Efficient Evaluation Functions for Evolving Coordination
    A. Agogino and K. Tumer
    Journal: Evol. Comput. [ bibtex ] [ pdf ]

  3. Applications of ensemble methods
    N. Oza and K. Tumer
    Journal: Inf. Fusion [ bibtex ] [ pdf ]

  4. Classifier ensembles: Select real-world applications
    N. Oza and K. Tumer
    Journal: Inf. Fusion [ bibtex ] [ pdf ]

  5. Ensemble clustering with voting active clusters
    K. Tumer and A. Agogino
    Journal: Pattern Recognit. Lett. [ bibtex ] [ pdf ]

  6. Adaptive Management of Air Traffic Flow: A Multiagent Coordination Approach
    K. Tumer and A. Agogino
    Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, AAAI 2008, Chicago, Illinois, USA, July 13-17, 2008 [ bibtex ] [ pdf ]

  7. Regulating air traffic flow with coupled agents
    A. Agogino and K. Tumer
    7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 2 [ bibtex ] [ pdf ]

  8. Aligning social welfare and agent preferences to alleviate traffic congestion
    K. Tumer, Z. Welch, and A. Agogino
    7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 2 [ bibtex ] [ pdf ]

2007

  1. Distributed agent-based air traffic flow management
    K. Tumer and A. Agogino
    6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007), Honolulu, Hawaii, USA, May 14-18, 2007 [ bibtex ] [ pdf ]

  2. Evolving distributed agents for managing air traffic
    A. Agogino and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2007, Proceedings, London, England, UK, July 7-11, 2007 [ bibtex ] [ pdf ]

  3. Evolving Multi Rover Systems in Dynamic and Noisy Environments
    K. Tumer and A. Agogino
    Evolutionary Computation in Dynamic and Uncertain Environments [ bibtex ] [ pdf ]

2006

  1. Handling Communication Restrictions and Team Formation in Congestion Games
    A. Agogino and K. Tumer
    Journal: Auton. Agents Multi Agent Syst. [ bibtex ] [ pdf ]

  2. QUICR-Learning for Multi-Agent Coordination
    A. Agogino and K. Tumer
    Proceedings, The Twenty-First National Conference on Artificial Intelligence and the Eighteenth Innovative Applications of Artificial Intelligence Conference, July 16-20, 2006, Boston, Massachusetts, USA [ bibtex ] [ pdf ]

  3. Efficient agent-based models for non-genomic evolution
    N. Gupta, A. Agogino, and K. Tumer
    5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, May 8-12, 2006 [ bibtex ] [ pdf ]

  4. Efficient agent-based cluster ensembles
    A. Agogino and K. Tumer
    5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, May 8-12, 2006 [ bibtex ] [ pdf ]

  5. Coordinating simple and unreliable agents
    K. Tumer
    5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), Hakodate, Japan, May 8-12, 2006 [ bibtex ] [ pdf ]

  6. Distributed evaluation functions for fault tolerant multi-rover systems
    A. Agogino and K. Tumer
    Genetic and Evolutionary Computation Conference, GECCO 2006, Proceedings, Seattle, Washington, USA, July 8-12, 2006 [ bibtex ] [ pdf ]

2005

  1. Multi-agent reward analysis for learning in noisy domains
    A. Agogino and K. Tumer
    4th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005), July 25-29, 2005, Utrecht, The Netherlands [ bibtex ] [ pdf ]

  2. Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments
    K. Tumer and A. Agogino
    Genetic and Evolutionary Computation Conference, GECCO 2005, Proceedings, Washington DC, USA, June 25-29, 2005 [ bibtex ] [ pdf ]

  3. Efficient credit assignment through evaluation function decomposition
    A. Agogino, K. Tumer, and R. Miikkulainen
    Genetic and Evolutionary Computation Conference, GECCO 2005, Proceedings, Washington DC, USA, June 25-29, 2005 [ bibtex ] [ pdf ]

  4. Efficient Reward Functions for Adaptive Multi-rover Systems
    K. Tumer and A. Agogino
    Learning and Adaption in Multi-Agent Systems, First International Workshop, LAMAS 2005, Utrecht, The Netherlands, July 25, 2005, Revised Selected Papers [ bibtex ] [ pdf ]

2004

  1. Unifying Temporal and Structural Credit Assignment Problems
    A. Agogino and K. Tumer
    3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), 19-23 August 2004, New York, NY, USA [ bibtex ] [ pdf ]

  2. Time-Extended Policies in Multi-Agent Reinforcement Learning
    K. Tumer and A. Agogino
    3rd International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2004), 19-23 August 2004, New York, NY, USA [ bibtex ] [ pdf ]

  3. Efficient Evaluation Functions for Multi-rover Systems
    A. Agogino and K. Tumer
    Genetic and Evolutionary Computation - GECCO 2004, Genetic and Evolutionary Computation Conference, Seattle, WA, USA, June 26-30, 2004, Proceedings, Part I [ bibtex ] [ pdf ]

2003

  1. Input decimated ensembles
    K. Tumer and N. Oza
    Journal: Pattern Anal. Appl. [ bibtex ] [ pdf ]

  2. Providing Effective Access to Shared Resources: A COIN Approach
    S. Airiau, S. Sen, D. Wolpert, and K. Tumer
    Engineering Self-Organising Systems, Nature-Inspired Approaches to Software Engineering [revised and extended papers presented at the Engineering Self-Organising Applications Workshop, ESOA 2003, held at AAMAS 2003 in Melbourne, Australia, in July 2003 and selected invited papers from leading researchers in self-organisation] [ bibtex ] [ pdf ]

  3. Team formation and communication restrictions in collectives
    A. Agogino and K. Tumer
    The Second International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2003, July 14-18, 2003, Melbourne, Victoria, Australia, Proceedings [ bibtex ] [ pdf ]

  4. Collectives for multiple resource job scheduling across heterogeneous servers
    K. Tumer and J. Lawson
    The Second International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2003, July 14-18, 2003, Melbourne, Victoria, Australia, Proceedings [ bibtex ] [ pdf ]

  5. Classification of Aircraft Maneuvers for Fault Detection
    N. Oza, K. Tumer, I. Tumer, and E. Huff
    Multiple Classifier Systems, 4th International Workshop, MCS 2003, Guilford, UK, June 11-13, 2003, Proceedings [ bibtex ] [ pdf ]

  6. Collectives for the Optimal Combination of Imperfect Objects
    K. Tumer and D. Wolpert
    Journal: CoRR [ bibtex ] [ pdf ]

  7. Improving Search Algorithms by Using Intelligent Coordinates
    D. Wolpert, K. Tumer, and E. Bandari
    Journal: CoRR [ bibtex ] [ pdf ]

2002

  1. The 2002 AAAI Spring Symposium Series
    J. Karlgren, P. Kanerva, B. Gambäck, K. Forbus, K. Tumer, P. Stone, K. Goebel, G. Sukhatme, T. Balch, B. Fischer, D. Smith, S. Harabagiu, V. Chaudri, M. Barley, H. Guesgen, T. Stahovich, R. Davis, and J. Landay
    Journal: AI Mag. [ bibtex ] [ pdf ]

  2. Collective Intelligence, Data Routing and Braess’ Paradox
    D. Wolpert and K. Tumer
    Journal: J. Artif. Intell. Res. [ bibtex ] [ pdf ]

  3. Robust Combining of Disparate Classifiers through Order Statistics
    K. Tumer and J. Ghosh
    Journal: Pattern Anal. Appl. [ bibtex ] [ pdf ]

  4. Learning sequences of actions in collectives of autonomous agents
    K. Tumer, A. Agogino, and D. Wolpert
    The First International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2002, July 15-19, 2002, Bologna, Italy, Proceedings [ bibtex ] [ pdf ]

2001

  1. Optimal Payoff Functions for Members of Collectives
    D. Wolpert and K. Tumer
    Journal: Adv. Complex Syst. [ bibtex ] [ pdf ]

  2. Reinforcement Learning in Distributed Domains: Beyond Team Games
    D. Wolpert, J. Sill, and K. Tumer
    Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, IJCAI 2001, Seattle, Washington, USA, August 4-10, 2001

  3. Input Decimation Ensembles: Decorrelation through Dimensionality Reduction
    N. Oza and K. Tumer
    Multiple Classifier Systems, Second International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001, Proceedings [ bibtex ] [ pdf ]

2000

  1. Collective Intelligence and Braess’ Paradox
    K. Tumer and D. Wolpert
    Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30 - August 3, 2000, Austin, Texas, USA [ bibtex ] [ pdf ]

  2. Adaptivity in agent-based routing for data networks
    D. Wolpert, S. Kirshner, C. Merz, and K. Tumer
    Proceedings of the Fourth International Conference on Autonomous Agents, AGENTS 2000, Barcelona, Catalonia, Spain, June 3-7, 2000 [ bibtex ] [ pdf ]

1999

  1. General Principles of Learning-Based Multi-Agent Systems
    D. Wolpert, K. Wheeler, and K. Tumer
    Proceedings of the Third Annual Conference on Autonomous Agents, AGENTS 1999, Seattle, WA, USA, May 1-5, 1999 [ bibtex ] [ pdf ]

  2. Avoiding Braess’ Paradox through Collective Intelligence
    K. Tumer and D. Wolpert
    Journal: CoRR [ bibtex ] [ pdf ]

  3. Using Collective Intelligence to Route Internet Traffic
    D. Wolpert, K. Tumer, and J. Frank
    Journal: CoRR [ bibtex ] [ pdf ]

  4. Robust Combining of Disparate Classifiers through Order Statistics
    K. Tumer and J. Ghosh
    Journal: CoRR [ bibtex ] [ pdf ]

  5. Collective Intelligence for Control of Distributed Dynamical Systems
    D. Wolpert, K. Wheeler, and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

  6. An Introduction to Collective Intelligence
    D. Wolpert and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

  7. General Principles of Learning-Based Multi-Agent Systems
    D. Wolpert, K. Wheeler, and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

  8. Adaptivity in Agent-Based Routing for Data Networks
    D. Wolpert, S. Kirshner, C. Merz, and K. Tumer
    Journal: CoRR [ bibtex ] [ pdf ]

  9. Ensembles of Radial Basis Function Networks for Spectroscopic Detection of Cervical Pre-Cancer
    K. Tumer, N. Ramanujam, J. Ghosh, and R. Richards-Kortum
    Journal: CoRR [ bibtex ] [ pdf ]

  10. Linear and Order Statistics Combiners for Pattern Classification
    K. Tumer and J. Ghosh
    Journal: CoRR [ bibtex ] [ pdf ]

1998

  1. Using Collective Intelligence to Route Internet Traffic
    D. Wolpert, K. Tumer, and J. Frank
    Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30 - December 5, 1998] [ bibtex ] [ pdf ]

1996

  1. Error Correlation and Error Reduction in Ensemble Classifiers
    K. Tumer and J. Ghosh
    Journal: Connect. Sci. [ bibtex ] [ pdf ]

  2. Analysis of decision boundaries in linearly combined neural classifiers
    K. Tumer and J. Ghosh
    Journal: Pattern Recognit. [ bibtex ] [ pdf ]

  3. Estimating the Bayes error rate through classifier combining
    K. Tumer and J. Ghosh
    13th International Conference on Pattern Recognition, ICPR 1996, Vienna, Austria, 25-19 August, 1996 [ bibtex ] [ pdf ]

  4. Spectroscopic Detection of Cervical Pre-Cancer through Radial Basis Function Networks
    K. Tumer, N. Ramanujam, R. Richards-Kortum, and J. Ghosh
    Advances in Neural Information Processing Systems 9, NIPS, Denver, CO, USA, December 2-5, 1996 [ bibtex ] [ pdf ]

1995

  1. Designing genetic algorithms for the state assignment problem
    J. Amaral, K. Tumer, and J. Ghosh
    Journal: IEEE Trans. Syst. Man Cybern. [ bibtex ] [ pdf ]

1994

  1. Sequence Recognition by Input Anticipation
    K. Tumer and J. Ghosh
    Proceedings of the Seventh International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1994, May 31-June 3, 1994, Austin, TX, USA [ bibtex ] [ pdf ]