Heuristic multiagent planning with self-interested agents. - Matt Crosby; Michael Rovatsos (AAMAS, 2011)

Automated Agent Decomposition for Classical Planning. - Matt Crosby; Michael Rovatsos; Ronald P. A. Petrick (ICAPS, 2013)

A Single-Agent Approach to Multiagent Planning. - Matthew Crosby; Anders Jonsson 001; Michael Rovatsos (ECAI, 2014)

Multiagent classical planning. - Matthew David Crosby (2014)

Integrating Mission, Logistics, and Task Planning for Skills-Based Robot Control in Industrial Kitting Applications. - Matthew Crosby; Ronald P. A. Petrick; César Toscano; Rui Correia Dias; Francesco Rovida; Volker Krüger (PlanSIG, 2016)

A Vertical and Cyber-Physical Integration of Cognitive Robots in Manufacturing. - Volker Krüger; Arnaud Chazoule; Matthew Crosby; Antoine Lasnier; Mikkel Rath Pedersen; Francesco Rovida; Lazaros Nalpantidis; Ronald P. A. Petrick; Cesar Toscano; Germano Veiga (Proc. IEEE, 2016)

Integrating Mission and Task Planning in an Industrial Robotics Framework. - Matthew Crosby; Ronald P. A. Petrick; Francesco Rovida; Volker Krüger (ICAPS, 2017)

Mapping Intelligence: Requirements and Possibilities. - Sankalp Bhatnagar; Anna Alexandrova; Shahar Avin; Stephen Cave; Lucy Cheke; Matthew Crosby; Jan Feyereisl; Marta Halina; Bao Sheng Loe; Seán Ó hÉigeartaigh; Fernando Martínez-Plumed; Huw Price; et al. (PT-AI, 2017)

Why Artificial Consciousness Matters. - Matthew Crosby (AAAI Spring Symposium: Towards Conscious AI Systems, 2019)

The Animal-AI Testbed and Competition. - Matthew Crosby; Benjamin Beyret; Murray Shanahan; José Hernández-Orallo; Lucy Cheke; Marta Halina (NeurIPS (Competition and Demos), 2019)

The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition. - Benjamin Beyret; José Hernández-Orallo; Lucy Cheke; Marta Halina; Murray Shanahan; Matthew Crosby (CoRR, 2019)

The Animal-AI Olympics. - Matthew Crosby; Benjamin Beyret; Marta Halina (Nat. Mach. Intell., 2019)

Episodic Memory for Learning Subjective-Timescale Models. - Alexey Zakharov; Matthew Crosby; Zafeirios Fountas (CoRR, 2020)

Special Issue "On Defining Artificial Intelligence" - Commentaries and Author's Response. - Dagmar Monett; Colin W. P. Lewis; Kristinn R. Thórisson; Joscha Bach; Gianluca Baldassarre; Giovanni Granato; Istvan S. N. Berkeley; François Chollet; Matthew Crosby; Henry Shevlin; John F. Sowa; John E. Laird; et al. (J. Artif. Gen. Intell., 2020)

Building Thinking Machines by Solving Animal Cognition Tasks. - Matthew Crosby (Minds Mach., 2020)

Fixed β-VAE Encoding for Curious Exploration in Complex 3D Environments. - Auguste Lehuger; Matthew Crosby (CoRR, 2021)

The Societal Implications of Deep Reinforcement Learning. - Jess Whittlestone; Kai Arulkumaran; Matthew Crosby (J. Artif. Intell. Res., 2021)

Limits and risks of GPT-3 applications. - Anna Strasser; Matthew Crosby; Eric Schwitzgebel (CogSci, 2022)

Detect, Understand, Act: A Neuro-Symbolic Hierarchical Reinforcement Learning Framework (Extended Abstract). - Ludovico Mitchener; David Tuckey; Matthew Crosby; Alessandra Russo (IJCAI, 2022)

How Far Can We Get in Creating a Digital Replica of a Philosopher? - Anna Strasser; Matthew Crosby; Eric Schwitzgebel (Robophilosophy, 2022)

Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework. - Ludovico Mitchener; David Tuckey; Matthew Crosby; Alessandra Russo (Mach. Learn., 2022)

Animal-AI 3: What's New & Why You Should Care. - Konstantinos Voudouris; Ibrahim Alhas; Wout Schellaert; Matthew Crosby; Joel Holmes; John Burden; Niharika Chaubey; Niall Donnelly; Matishalin Patel; Marta Halina; José Hernández-Orallo; Lucy G. Cheke (CoRR, 2023)

Synergistic information supports modality integration and flexible learning in neural networks solving multiple tasks. - Alexandra M. Proca; Fernando E. Rosas; Andrea I. Luppi; Daniel Bor; Matthew Crosby; Pedro A. M. Mediano (PLoS Comput. Biol., 2024)