Matthew Crosby
Matthew Crosby
Imperial College London
Verified email at - Homepage
Cited by
Cited by
SkiROS—a skill-based robot control platform on top of ROS
F Rovida, M Crosby, D Holz, AS Polydoros, B Großmann, RPA Petrick, ...
Robot Operating System (ROS) The Complete Reference (Volume 2), 121-160, 2017
Automated agent decomposition for classical planning
M Crosby, M Rovatsos, R Petrick
Proceedings of the International Conference on Automated Planning and …, 2013
The limits of machine intelligence: Despite progress in machine intelligence, artificial general intelligence is still a major challenge
H Shevlin, K Vold, M Crosby, M Halina
EMBO reports 20 (10), e49177, 2019
Introduction to the JAGI special issue ‘On defining artificial intelligence’–commentaries and author’s response
D Monett, CW Lewis, KR Thórisson, J Bach, G Baldassarre, G Granato, ...
Journal of Artificial General Intelligence 11 (2), 1-100, 2020
A Single-Agent Approach to Multiagent Planning.
M Crosby, A Jonsson, M Rovatsos
ECAI, 237-242, 2014
The Animal-AI Olympics
M Crosby, B Beyret, M Halina
Nature Machine Intelligence 1 (5), 257, 2019
A vertical and cyber–physical integration of cognitive robots in manufacturing
V Krueger, A Chazoule, M Crosby, A Lasnier, MR Pedersen, F Rovida, ...
Proceedings of the IEEE 104 (5), 1114-1127, 2016
Mapping intelligence: Requirements and possibilities
S Bhatnagar, A Alexandrova, S Avin, S Cave, L Cheke, M Crosby, ...
Philosophy and theory of artificial intelligence 2017, 117-135, 2018
The societal implications of deep reinforcement learning
J Whittlestone, K Arulkumaran, M Crosby
Journal of Artificial Intelligence Research 70, 1003–1030-1003–1030, 2021
Artificial intelligence and the common sense of animals
M Shanahan, M Crosby, B Beyret, L Cheke
Trends in cognitive sciences 24 (11), 862-872, 2020
Testing the vertical and cyber-physical integration of cognitive robots in manufacturing
V Krueger, F Rovida, B Grossmann, R Petrick, M Crosby, A Charzoule, ...
Robotics and Computer-Integrated Manufacturing 57, 213-219, 2019
The animal-AI testbed and competition
M Crosby, B Beyret, M Shanahan, J Hernández-Orallo, L Cheke, M Halina
Neurips 2019 competition and demonstration track, 164-176, 2020
Building thinking machines by solving animal cognition tasks
M Crosby
Minds and Machines 30 (4), 589-615, 2020
The animal-ai environment: Training and testing animal-like artificial cognition
B Beyret, J Hernández-Orallo, L Cheke, M Halina, M Shanahan, M Crosby
arXiv preprint arXiv:1909.07483, 2019
Integrating Mission and Task Planning in an Industrial Robotics Framework
M Crosby, F Rovida, V Krüger, RPA Petrick
Proceedings of the 27th International Conference on Automated Planning and …, 2017
Temporal multiagent planning with concurrent action constraints
M Crosby, RPA Petrick
Proc 2nd ICAPS Workshop on Distributed and Multi-Agent Planning. ICAPS, 16-24, 2014
Heuristic multiagent planning with self-interested agents
M Crosby, M Rovatsos
The 10th International Conference on Autonomous Agents and Multiagent …, 2011
Detect, understand, act: A neuro-symbolic hierarchical reinforcement learning framework
L Mitchener, D Tuckey, M Crosby, A Russo
Machine Learning 111 (4), 1523-1549, 2022
Adp an agent decomposition planner codmap 2015
M Crosby
Competition of Distributed and Multi-Agent Planners (CoDMAP-15), 4, 2015
Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks
AM Proca, FE Rosas, AI Luppi, D Bor, M Crosby, PAM Mediano
arXiv preprint arXiv:2210.02996, 2022
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