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ORCIDAdrian K. Agogino
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2020 – today
- 2021
[j16]Andrew P. Sabelhaus
, Huajing Zhao, Edward L. Zhu, Adrian K. Agogino, Alice M. Agogino:
Model-Predictive Control With Inverse Statics Optimization for Tensegrity Spine Robots. IEEE Trans. Control. Syst. Technol. 29(1): 263-277 (2021)- 2020
- [j15]Andrew P. Sabelhaus, Albert H. Li, Kimberly A. Sover, Jacob R. Madden, Andrew R. Barkan, Adrian K. Agogino, Alice M. Agogino:
Inverse Statics Optimization for Compound Tensegrity Robots. IEEE Robotics Autom. Lett. 5(3): 3982-3989 (2020)
2010 – 2019
- 2018
- [i6]Andrew P. Sabelhaus, Lara Janse van Vuuren, Ankita Joshi, Edward Zhu, Hunter J. Garnier, Kimberly A. Sover, Jesús Navarro, Adrian K. Agogino, Alice M. Agogino:
Design, Simulation, and Testing of Laika, a Quadruped Robot with a Flexible Actuated Spine. CoRR abs/1804.06527 (2018) - [i5]Andrew P. Sabelhaus, Huajing Zhao, Edward L. Zhu, Adrian K. Agogino, Alice M. Agogino:
Model-Predictive Control with Reference Input Tracking for Tensegrity Spine Robots. CoRR abs/1806.08868 (2018) - [i4]Andrew P. Sabelhaus, Adrian K. Agogino:
Inverse Kinematics for Control of Tensegrity Soft Robots: Existence and Optimality of Solutions. CoRR abs/1808.08252 (2018) - 2017
- [c46]Steven Lessard, Pattawong Pansodtee, Ash Robbins, Leya Breanna Baltaxe-Admony, James M. Trombadore, Mircea Teodorescu, Adrian K. Agogino, Sri Kurniawan:
CRUX: A compliant robotic upper-extremity exosuit for lightweight, portable, multi-joint muscular augmentation. ICORR 2017: 1633-1638 - [c45]Lee-Huang Chen, Brian Cera, Edward L. Zhu, Riley Edmunds, Franklin Rice, Antonia Bronars, Ellande Tang, Saunon R. Malekshahi, Osvaldo Romero, Adrian K. Agogino, Alice M. Agogino:
Inclined surface locomotion strategies for spherical tensegrity robots. IROS 2017: 4976-4981 - [i3]Lee-Huang Chen, Brian Cera, Edward L. Zhu, Riley Edmunds, Franklin Rice, Antonia Bronars, Ellande Tang, Saunon R. Malekshahi, Osvaldo Romero, Adrian K. Agogino, Alice M. Agogino:
Inclined Surface Locomotion Strategies for Spherical Tensegrity Robots. CoRR abs/1708.08150 (2017) - 2016
- [j14]Chris HolmesParker, Adrian K. Agogino, Kagan Tumer:
Combining reward shaping and hierarchies for scaling to large multiagent systems. Knowl. Eng. Rev. 31(1): 3-18 (2016) - [c44]Steven Lessard, Jonathan Bruce, Erik Jung, Mircea Teodorescu, Vytas SunSpiral, Adrian K. Agogino:
A lightweight, multi-axis compliant tensegrity joint. ICRA 2016: 630-635 - [c43]Kyunam Kim, Lee-Huang Chen, Brian Cera, Mallory Daly, Edward Zhu, Julien Despois, Adrian K. Agogino, Vytas SunSpiral, Alice M. Agogino:
Hopping and rolling locomotion with spherical tensegrity robots. IROS 2016: 4369-4376 - [c42]Steven Lessard, Dennis Castro, William Asper, Shaurya Deep Chopra, Leya Breanna Baltaxe-Admony, Mircea Teodorescu, Vytas SunSpiral, Adrian K. Agogino:
A bio-inspired tensegrity manipulator with multi-DOF, structurally compliant joints. IROS 2016: 5515-5520 - [i2]Steven Lessard, Dennis Castro, William Asper, Shaurya Deep Chopra, Leya Breanna Baltaxe-Admony, Mircea Teodorescu, Vytas SunSpiral, Adrian K. Agogino:
A Bio-Inspired Tensegrity Manipulator with Multi-DOF, Structurally Compliant Joints. CoRR abs/1604.08667 (2016) - 2015
- [j13]Atil Iscen, Ken Caluwaerts, Jonathan Bruce, Adrian K. Agogino, Vytas SunSpiral, Kagan Tumer:
Learning Tensegrity Locomotion Using Open-Loop Control Signals and Coevolutionary Algorithms. Artif. Life 21(2): 119-140 (2015) - [j12]Logan Michael Yliniemi, Adrian K. Agogino, Kagan Tumer:
Simulation of the introduction of new technologies in air traffic management. Connect. Sci. 27(3): 269-287 (2015) - [c41]Kyunam Kim, Adrian K. Agogino, Aliakbar Toghyan, Deaho Moon, Laqshya Taneja, Alice M. Agogino:
Robust learning of tensegrity robot control for locomotion through form-finding. IROS 2015: 5824-5831 - [i1]Steven Lessard, Jonathan Bruce, Erik Jung, Mircea Teodorescu, Vytas SunSpiral, Adrian K. Agogino:
A light-weight, multi-axis compliant tensegrity joint. CoRR abs/1510.07595 (2015) - 2014
- [j11]Logan Michael Yliniemi, Adrian K. Agogino, Kagan Tumer:
Multirobot Coordination for Space Exploration. AI Mag. 35(4): 61-74 (2014) - [c40]Chris HolmesParker, Matthew E. Taylor, Adrian K. Agogino, Kagan Tumer:
CLEANing the reward: counterfactual actions to remove exploratory action noise in multiagent learning (extended abstract). AAMAS 2014: 1353-1354 - [c39]William J. Curran, Adrian K. Agogino, Kagan Tumer:
Using reward/utility based impact scores in partitioning. AAMAS 2014: 1563-1564 - [c38]William J. Curran, Adrian K. Agogino, Kagan Tumer:
Hierarchical simulation for complex domains: air traffic flow management. GECCO 2014: 1087-1094 - [c37]Logan Michael Yliniemi, Adrian K. Agogino, Kagan Tumer:
Evolutionary agent-based simulation of the introduction of new technologies in air traffic management. GECCO 2014: 1215-1222 - [c36]Atil Iscen, Adrian K. Agogino, Vytas SunSpiral, Kagan Tumer:
Flop and roll: Learning robust goal-directed locomotion for a Tensegrity Robot. IROS 2014: 2236-2243 - [c35]Kyunam Kim, Adrian K. Agogino, Deaho Moon, Laqshya Taneja, Aliakbar Toghyan, Borna Dehghani, Vytas SunSpiral, Alice M. Agogino:
Rapid prototyping design and control of tensegrity soft robot for locomotion. ROBIO 2014: 7-14 - [c34]Chris HolmesParker, Matthew E. Taylor, Adrian K. Agogino, Kagan Tumer:
CLEAN Rewards to Improve Coordination by Removing Exploratory Action Noise. WI-IAT (3) 2014: 127-134 - 2013
- [c33]Chris HolmesParker, Adrian K. Agogino, Kagan Tumer:
CLEAN rewards for improving multiagent coordination in the presence of exploration. AAMAS 2013: 1113-1114 - [c32]Chris HolmesParker, Adrian K. Agogino, Kagan Tumer:
Exploiting structure and utilizing agent-centric rewards to promote coordination in large multiagent systems. AAMAS 2013: 1181-1182 - [c31]Atil Iscen, Adrian K. Agogino, Vytas SunSpiral, Kagan Tumer:
Learning to control complex tensegrity robots. AAMAS 2013: 1193-1194 - [c30]William J. Curran, Adrian K. Agogino, Kagan Tumer:
Addressing hard constraints in the air traffic problem through partitioning and difference rewards. AAMAS 2013: 1281-1282 - [c29]William J. Curran, Adrian K. Agogino, Kagan Tumer:
Partitioning agents and shaping their evaluation functions in air traffic problems with hard constraints. GECCO (Companion) 2013: 183-184 - [c28]Atil Iscen, Adrian K. Agogino, Vytas SunSpiral, Kagan Tumer:
Controlling tensegrity robots through evolution. GECCO 2013: 1293-1300 - 2012
- [j10]Adrian K. Agogino, Kagan Tumer:
A multiagent approach to managing air traffic flow. Auton. Agents Multi Agent Syst. 24(1): 1-25 (2012) - [c27]Adrian K. Agogino, Chris HolmesParker, Kagan Tumer:
Evolving distributed resource sharing for cubesat constellations. GECCO 2012: 1015-1022 - [c26]Adrian K. Agogino, Chris HolmesParker, Kagan Tumer:
Evolving large scale UAV communication system. GECCO 2012: 1023-1030 - 2011
- [c25]Chris HolmesParker, Adrian K. Agogino:
Agent-based resource allocation in dynamically formed CubeSat constellations. AAMAS 2011: 1157-1158 - 2010
- [j9]Adrian K. Agogino, Kagan Tumer:
A Multiagent Coordination Approach to Robust Consensus Clustering. Adv. Complex Syst. 13(2): 165-197 (2010) - [c24]Adrian K. Agogino:
Component evolution for large scale air traffic optimization. GECCO (Companion) 2010: 2059-2060
2000 – 2009
- 2009
- [j8]Kagan Tumer, Adrian K. Agogino:
Multiagent Learning for Black Box System Reward Functions. Adv. Complex Syst. 12(4-5): 475-492 (2009) - [j7]Adrian K. Agogino, Kagan Tumer:
Learning Indirect Actions in Complex Domains: Action Suggestions for Air Traffic Control. Adv. Complex Syst. 12(4-5): 493-512 (2009) - [j6]Kagan Tumer, Adrian K. Agogino:
Improving Air Traffic Management with a Learning Multiagent System. IEEE Intell. Syst. 24(1): 18-21 (2009) - [c23]Adrian K. Agogino, Kagan Tumer:
Improving air traffic management through agent suggestions. AAMAS (2) 2009: 1271-1272 - [c22]Adrian K. Agogino:
Evaluating evolution and monte carlo for controlling air traffic flow. GECCO (Companion) 2009: 1957-1962 - [p2]Kagan Tumer, Zachary T. Welch, Adrian K. Agogino:
Traffic Congestion Management as a Learning Agent Coordination Problem. Multi-Agent Systems for Traffic and Transportation Engineering 2009: 261-279 - 2008
- [j5]Adrian K. Agogino, Kagan Tumer:
Analyzing and visualizing multiagent rewards in dynamic and stochastic domains. Auton. Agents Multi Agent Syst. 17(2): 320-338 (2008) - [j4]Adrian K. Agogino, Kagan Tumer:
Efficient Evaluation Functions for Evolving Coordination. Evol. Comput. 16(2): 257-288 (2008) - [j3]Kagan Tumer, Adrian K. Agogino:
Ensemble clustering with voting active clusters. Pattern Recognit. Lett. 29(14): 1947-1953 (2008) - [c21]Kagan Tumer, Adrian K. Agogino:
Adaptive Management of Air Traffic Flow: A Multiagent Coordination Approach. AAAI 2008: 1581-1584 - [c20]Adrian K. Agogino, Kagan Tumer:
Regulating air traffic flow with coupled agents. AAMAS (2) 2008: 535-542 - [c19]Kagan Tumer, Zachary T. Welch, Adrian K. Agogino:
Aligning social welfare and agent preferences to alleviate traffic congestion. AAMAS (2) 2008: 655-662 - 2007
- [c18]Kagan Tumer, Adrian K. Agogino:
Distributed agent-based air traffic flow management. AAMAS 2007: 255 - [c17]Adrian K. Agogino, Kagan Tumer:
Evolving distributed agents for managing air traffic. GECCO 2007: 1888-1895 - [p1]Kagan Tumer, Adrian K. Agogino:
Evolving Multi Rover Systems in Dynamic and Noisy Environments. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 371-387 - 2006
- [j2]Adrian K. Agogino, Kagan Tumer:
Handling Communication Restrictions and Team Formation in Congestion Games. Auton. Agents Multi Agent Syst. 13(1): 97-115 (2006) - [c16]Adrian K. Agogino, Kagan Tumer:
QUICR-Learning for Multi-Agent Coordination. AAAI 2006: 1438-1443 - [c15]Nachi Gupta, Adrian K. Agogino, Kagan Tumer:
Efficient agent-based models for non-genomic evolution. AAMAS 2006: 58-64 - [c14]Adrian K. Agogino, Kagan Tumer:
Efficient agent-based cluster ensembles. AAMAS 2006: 1079-1086 - [c13]Adrian K. Agogino, Kagan Tumer:
Distributed evaluation functions for fault tolerant multi-rover systems. GECCO 2006: 1079-1086 - 2005
- [c12]Adrian K. Agogino, Kagan Tumer:
Multi-agent reward analysis for learning in noisy domains. AAMAS 2005: 81-88 - [c11]Kagan Tumer, Adrian K. Agogino:
Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments. GECCO 2005: 591-598 - [c10]Adrian K. Agogino, Kagan Tumer, Risto Miikkulainen:
Efficient credit assignment through evaluation function decomposition. GECCO 2005: 1309-1316 - [c9]Kagan Tumer, Adrian K. Agogino:
Efficient Reward Functions for Adaptive Multi-rover Systems. LAMAS 2005: 177-191 - 2004
- [c8]Adrian K. Agogino, Kagan Tumer:
Unifying Temporal and Structural Credit Assignment Problems. AAMAS 2004: 980-987 - [c7]Kagan Tumer, Adrian K. Agogino:
Time-Extended Policies in Multi-Agent Reinforcement Learning. AAMAS 2004: 1338-1339 - [c6]Adrian K. Agogino, Kagan Tumer:
Efficient Evaluation Functions for Multi-rover Systems. GECCO (1) 2004: 1-11 - [c5]Kagan Tumer, Adrian K. Agogino:
Overcoming communication restrictions in collectives. IJCNN 2004: 1127-1132 - 2003
- [c4]Adrian K. Agogino, Kagan Tumer:
Team formation and communication restrictions in collectives. AAMAS 2003: 916-917 - 2002
- [c3]Kagan Tumer, Adrian K. Agogino, David H. Wolpert:
Learning sequences of actions in collectives of autonomous agents. AAMAS 2002: 378-385 - 2000
- [j1]Adrian K. Agogino, Kenneth O. Stanley, Risto Miikkulainen:
Online Interactive Neuro-evolution. Neural Process. Lett. 11(1): 29-38 (2000) - [c2]Adrian K. Agogino, Joydeep Ghosh, Stavros J. Perantonis, Vassilis Virvilis, Sergios Petridis, Paulo J. G. Lisboa:
The Role of Multiple, Linear-Projection Based Visualization Techniques in RBF-Based Classification of High Dimensional Data. IJCNN (3) 2000: 47-52
1990 – 1999
- 1999
- [c1]Adrian K. Agogino, Joydeep Ghosh, Cheryl E. Martin:
Visualization of radial basis function networks. IJCNN 1999: 1199-1202
Coauthor Index
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