Grammar-based autonomous discovery of abstractions for evolution of complex multi-agent behaviours

[1]  Jun Zhu,et al.  Deep reinforcement learning with credit assignment for combinatorial optimization , 2021, Pattern Recognit..

[2]  Kathryn E. Kasmarik,et al.  Grammar-based cooperative learning for evolving collective behaviours in multi-agent systems , 2021, Swarm Evol. Comput..

[3]  Brida V. Mbuwir,et al.  Transfer learning in demand response: A review of algorithms for data-efficient modelling and control , 2021, Energy and AI.

[4]  Kathryn Kasmarik,et al.  Task Allocation in Multi-Agent Systems with Grammar-Based Evolution , 2021, IVA.

[5]  Kathryn E. Kasmarik,et al.  Exploiting abstractions for grammar‐based learning of complex multi‐agent behaviours , 2021, Int. J. Intell. Syst..

[6]  Wojciech Paszke,et al.  Robust PD-type iterative learning control for discrete systems with multiple time-delays subjected to polytopic uncertainty and restricted frequency-domain , 2021, Multidimens. Syst. Signal Process..

[7]  Huizhong Yang,et al.  Robust point‐to‐point iterative learning control with trial‐varying initial conditions , 2020, IET Control Theory & Applications.

[8]  Jing Xu,et al.  Learning Multi-Agent Coordination for Enhancing Target Coverage in Directional Sensor Networks , 2020, NeurIPS.

[9]  Shunkai Fu,et al.  Self-organizing neighborhood-based differential evolution for global optimization , 2020, Swarm Evol. Comput..

[10]  Yuhui Shi,et al.  A Parallel Evolutionary Algorithm with Value Decomposition for Multi-agent Problems , 2020, ICSI.

[11]  Gerd Ascheid,et al.  Evolving Instinctive Behaviour in Resource-Constrained Autonomous Agents Using Grammatical Evolution , 2020, EvoApplications.

[12]  Jorge Cortes,et al.  Hierarchical reinforcement learning via dynamic subspace search for multi-agent planning , 2019, Autonomous Robots.

[13]  Yue Xu,et al.  A Novel Multi-Agent Parallel-Critic Network Architecture for Cooperative-Competitive Reinforcement Learning , 2020, IEEE Access.

[14]  Thanh-Ha Le,et al.  A Hierarchical Deep Deterministic Policy Gradients for Swarm Navigation , 2019, 2019 11th International Conference on Knowledge and Systems Engineering (KSE).

[15]  Michael A. Goodrich,et al.  Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees , 2019, IJCAI.

[16]  Kathryn Kasmarik,et al.  Automatic synthesis of swarm behavioural rules from their atomic components , 2018, GECCO.

[17]  Pieter Abbeel,et al.  Meta Learning Shared Hierarchies , 2017, ICLR.

[18]  Shuai Li,et al.  Simultaneous learning and control of parallel Stewart platforms with unknown parameters , 2017, Neurocomputing.

[19]  Anthony Brabazon,et al.  Evolutionary Behavior Tree Approaches for Navigating Platform Games , 2017, IEEE Transactions on Computational Intelligence and AI in Games.

[20]  Alex Graves,et al.  Automated Curriculum Learning for Neural Networks , 2017, ICML.

[21]  Halife Kodaz,et al.  A novel parallel multi-swarm algorithm based on comprehensive learning particle swarm optimization , 2015, Eng. Appl. Artif. Intell..

[22]  Leonardo Trujillo,et al.  Generalization in Maze Navigation Using Grammatical Evolution and Novelty Search , 2014, TPNC.

[23]  Alastair Channon,et al.  Heterogeneous complexification strategies robustly outperform homogeneous strategies for incremental evolution , 2013, ECAL.

[24]  Eliseo Ferrante,et al.  GESwarm: grammatical evolution for the automatic synthesis of collective behaviors in swarm robotics , 2013, GECCO '13.

[25]  Sancho Oliveira,et al.  Hierarchical Reinforcement Learning: Learning sub-goals and state-abstraction , 2011, 6th Iberian Conference on Information Systems and Technologies (CISTI 2011).

[26]  Anthony Brabazon,et al.  Evolving Behaviour Trees for the Mario AI Competition Using Grammatical Evolution , 2011, EvoApplications.

[27]  Thomas Stützle,et al.  Incremental Social Learning in Particle Swarms , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[28]  Kaiqi Huang,et al.  An Extended Grammar System for Learning and Recognizing Complex Visual Events , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Qiang Yang,et al.  A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.

[30]  Alexandros Agapitos,et al.  Comparing the performance of the evolvable πGrammatical Evolution genotype-phenotype map to Grammatical Evolution in the dynamic Ms. Pac-Man environment , 2010, IEEE Congress on Evolutionary Computation.

[31]  Jason Weston,et al.  Curriculum learning , 2009, ICML '09.

[32]  M. O'Neill,et al.  Grammatical evolution , 2001, GECCO '09.

[33]  Stéphane Doncieux,et al.  Incremental Evolution of Animats' Behaviors as a Multi-objective Optimization , 2008, SAB.

[34]  Alcherio Martinoli,et al.  Parallel learning in heterogeneous multi-robot swarms , 2007, 2007 IEEE Congress on Evolutionary Computation.

[35]  Marco Dorigo,et al.  Incremental Evolution of Robot Controllers for a Highly Integrated Task , 2006, SAB.

[36]  Steven M. Gustafson,et al.  Genetic Programming And Multi-agent Layered Learning By Reinforcements , 2002, GECCO.

[37]  Olivier Buffet,et al.  Multi-Agent Systems by Incremental Gradient Reinforcement Learning , 2001, IJCAI.

[38]  Olivier Buffet,et al.  Incremental reinforcement learning for designing multi-agent systems , 2001, AGENTS '01.

[39]  Richard W. Longman,et al.  Iterative learning control and repetitive control for engineering practice , 2000 .

[40]  Michael O'Neill,et al.  Grammatical Evolution: Evolving Programs for an Arbitrary Language , 1998, EuroGP.

[41]  Corso Elvezia A General Method for Incremental Self-improvement and Multi-agent Learning in Unrestricted Environments , 1996 .

[42]  Takanori Shibata,et al.  Sensor-based behavior using a neural network for incremental learning in family mobile robot system , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[43]  Suguru Arimoto,et al.  Bettering operation of Robots by learning , 1984, J. Field Robotics.

[44]  Anas N. Al-Rabadi,et al.  A comparison of modified reconstructability analysis and Ashenhurst‐Curtis decomposition of Boolean functions , 2004 .

[45]  Marvin Minsky,et al.  Steps toward Artificial Intelligence , 1995, Proceedings of the IRE.