Abbas Abdolmaleki

Abdolmaleki, A., Price, B., Lau, N., Reis, L. and Neumann, G. (2017). Deriving and improving CMA-ES with information geometric trust regions. Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2017, Berlin, Germany, July 15-19, 2017 (pp. 657-664)

Abdolmaleki, A., Price, B., Lau, N., Reis, L. and Neumann, G. (2017). Contextual Covariance Matrix Adaptation Evolutionary Strategies. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017 (pp. 1378-1385)

Abdolmaleki, A., Lau, N., Reis, L. and Neumann, G. (2016). Non-Parametric Contextual Stochastic Search. 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016) (pp. 2643-2648)

Abdolmaleki, A., Lioutikov, R., Lau, N., Reis, L., Peters, J. and Neumann, G. (2016). Model-Based Relative Entropy Stochastic Search. PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO’16 COMPANION) (pp. 153-154)

Abdolmaleki, A., Simões, D., Lau, N., Reis, L. and Neumann, G. (2016). Learning a Humanoid Kick with Controlled Distance. RoboCup 2016: Robot World Cup XX [Leipzig, Germany, June 30 - July 4, 2016] (pp. 45-57)

Abdolmaleki, A., Lau, N., Reis, L. and Neumann, G. (2016). Contextual Stochastic Search. PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO’16 COMPANION) (pp. 29-30)

Abdolmaleki, A., Simoes, D., Lau, N., Reis, L. and Neumann, G. (2016). Contextual Relative Entropy Policy Search with Covariance Matrix Adaptation. 2016 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC 2016) (pp. 94-99)

Abdolmaleki, A., Lau, N., Reis, L., Peters, J. and Neumann, G. (2016). Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 83 (3-4), pp. 393-408

Abdolmaleki, A., Lau, N., Reis, L. and Neumann, G. (2015). Regularized Covariance Estimation for Weighted Maximum Likelihood Policy Search Methods. 2015 IEEE-RAS 15TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS) (pp. 154-159)

Abdolmaleki, A., Lioutikov, R., Peters, J., Lau, N., Reis, L. and Neumann, G. (2015). Model-Based Relative Entropy Stochastic Search. Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada (pp. 3537-3545)

Shafii, N., Abdolmaleki, A., Lau, N. and Reis, L. (2015). Development of an Omnidirectional Walk Engine for Soccer Humanoid Robots. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 12, pp. 1

Abdolmaleki, A., Lau, N., Reis, L., Peters, J. and Neumann, G. (2015). Contextual Policy Search for Generalizing a Parameterized Biped Walking Controller. 2015 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS (ICARSC) (pp. 17-22)

Abdolmaleki, A., Shafii, N., Reis, L., Lau, N., Peters, J. and Neumann, G. (2014). Omnidirectional Walking with a Compliant Inverted Pendulum Model. ADVANCES IN ARTIFICIAL INTELLIGENCE (IBERAMIA 2014) (pp. 481-493)

Shafii, N., Abdolmaleki, A., Ferreira, R., Lau, N. and Reis, L. (2013). Omnidirectional Walking and Active Balance for Soccer Humanoid Robot. PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2013 (pp. 283-294)

Ferreira, R., Shafii, N., Lau, N., Reis, L. and Abdolmaleki, A. (2013). Diagonal Walk Reference Generator based on Fourier Approximation of ZMP Trajectory. PROCEEDINGS OF THE 2013 13TH INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS (ROBOTICA)

Abdolmaleki, A., Movahedi, M., Lau, N. and Reis, L. (2013). A distributed cooperative reinforcement learning method for decision making in fire brigade teams. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 237-248)

Abdolmaleki, A., Movahedi, M., Salehi, S., Lau, N. and Reis, L. (2011). A Reinforcement Learning Based Method for Optimizing the Process of Decision Making in Fire Brigade Agents. PROGRESS IN ARTIFICIAL INTELLIGENCE (pp. 340-351)