Murray Shanahan

ORCID

Publication Activity (10 Years)

Years Active: 1987-2024
Publications (10 Years): 54

Top Venues

Publications

Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomasev, Ira Ktena, Zachary Kenton, Mikel Rodriguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sébastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agüera y Arcas, William Isaac, James Manyika
The Ethics of Advanced AI Assistants. CoRR (2024)
Murray Shanahan
Talking about Large Language Models. Commun. ACM 67 (2) (2024)
Seliem El-Sayed, Canfer Akbulut, Amanda McCroskery, Geoff Keeling, Zachary Kenton, Zaria Jalan, Nahema Marchal, Arianna Manzini, Toby Shevlane, Shannon Vallor, Daniel Susser, Matija Franklin, Sophie Bridgers, Harry Law, Matthew Rahtz, Murray Shanahan, Michael Henry Tessler, Arthur Douillard, Tom Everitt, Sasha Brown
A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI. CoRR (2024)
Murray Shanahan
Simulacra as Conscious Exotica. CoRR (2024)
Murray Shanahan, Catherine Clarke
Evaluating Large Language Model Creativity from a Literary Perspective. CoRR (2023)
Ole Jørgensen, Dylan Cope, Nandi Schoots, Murray Shanahan
Improving Activation Steering in Language Models with Mean-Centring. CoRR (2023)
Sivaramakrishnan Swaminathan, Antoine Dedieu, Rajkumar Vasudeva Raju, Murray Shanahan, Miguel Lázaro-Gredilla, Dileep George
Schema-learning and rebinding as mechanisms of in-context learning and emergence. CoRR (2023)
Antonia Creswell, Murray Shanahan, Irina Higgins
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning. ICLR (2023)
Murray Shanahan, Kyle McDonell, Laria Reynolds
Role-Play with Large Language Models. CoRR (2023)
Murray Shanahan, Kyle McDonell, Laria Reynolds
Role play with large language models. Nat. 623 (7987) (2023)
Sivaramakrishnan Swaminathan, Antoine Dedieu, Rajkumar Vasudeva Raju, Murray Shanahan, Miguel Lázaro-Gredilla, Dileep George
Schema-learning and rebinding as mechanisms of in-context learning and emergence. NeurIPS (2023)
Wilka Carvalho, Andrew Kyle Lampinen, Kyriacos Nikiforou, Felix Hill, Murray Shanahan
Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023)
Alex F. Spies, Alessandra Russo, Murray Shanahan
Sparse Relational Reasoning with Object-Centric Representations. CoRR (2022)
Antonia Creswell, Murray Shanahan, Irina Higgins
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning. CoRR (2022)
Murray Shanahan, Melanie Mitchell
Abstraction for Deep Reinforcement Learning. IJCAI (2022)
Borja G. León, Murray Shanahan, Francesco Belardinelli
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications. ICLR (2022)
Murray Shanahan, Melanie Mitchell
Abstraction for Deep Reinforcement Learning. CoRR (2022)
Zafeirios Fountas, Anastasia Sylaidi, Kyriacos Nikiforou, Anil K. Seth, Murray Shanahan, Warrick Roseboom
A Predictive Processing Model of Episodic Memory and Time Perception. Neural Comput. 34 (7) (2022)
Antonia Creswell, Murray Shanahan
Faithful Reasoning Using Large Language Models. CoRR (2022)
Murray Shanahan
Talking About Large Language Models. CoRR (2022)
Borja G. León, Murray Shanahan, Francesco Belardinelli
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications. CoRR (2021)
Antonia Creswell, Rishabh Kabra, Christopher Burgess, Murray Shanahan
Unsupervised Object-Based Transition Models for 3D Partially Observable Environments. CoRR (2021)
Wilka Carvalho, Andrew K. Lampinen, Kyriacos Nikiforou, Felix Hill, Murray Shanahan
Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning. CoRR (2021)
Murray Shanahan, Christos Kaplanis, Jovana Mitrovic
Encoders and Ensembles for Task-Free Continual Learning. CoRR (2021)
Antonia Creswell, Rishabh Kabra, Christopher P. Burgess, Murray Shanahan
Unsupervised Object-Based Transition Models For 3D Partially Observable Environments. NeurIPS (2021)
Antonia Creswell, Kyriacos Nikiforou, Oriol Vinyals, Andre Saraiva, Rishabh Kabra, Loic Matthey, Christopher Burgess, Malcolm Reynolds, Richard Tanburn, Marta Garnelo, Murray Shanahan
AlignNet: Unsupervised Entity Alignment. CoRR (2020)
Christos Kaplanis, Claudia Clopath, Murray Shanahan
Continual Reinforcement Learning with Multi-Timescale Replay. CoRR (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. ICML (2020)
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David G. T. Barrett, Marta Garnelo
An Explicitly Relational Neural Network Architecture. ICML (2020)
Daniel Pace, Alessandra Russo, Murray Shanahan
Learning Diverse Representations for Fast Adaptation to Distribution Shift. CoRR (2020)
Borja G. León, Murray Shanahan, Francesco Belardinelli
Systematic Generalisation through Task Temporal Logic and Deep Reinforcement Learning. CoRR (2020)
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules. CoRR (2020)
Benjamin Beyret, José Hernández-Orallo, Lucy Cheke, Marta Halina, Murray Shanahan, Matthew Crosby
The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition. CoRR (2019)
Christos Kaplanis, Murray Shanahan, Claudia Clopath
Policy Consolidation for Continual Reinforcement Learning. CoRR (2019)
Matthew Crosby, Benjamin Beyret, Murray Shanahan, José Hernández-Orallo, Lucy Cheke, Marta Halina
The Animal-AI Testbed and Competition. NeurIPS (Competition and Demos) (2019)
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David Barrett, Marta Garnelo
An Explicitly Relational Neural Network Architecture. CoRR (2019)
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. IEEE Trans. Neural Networks Learn. Syst. 30 (11) (2019)
Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, Peter W. Battaglia
Deep reinforcement learning with relational inductive biases. ICLR (Poster) (2019)
Christos Kaplanis, Murray Shanahan, Claudia Clopath
Policy Consolidation for Continual Reinforcement Learning. ICML (2019)
Christos Kaplanis, Murray Shanahan, Claudia Clopath
Continual Reinforcement Learning with Complex Synapses. ICML (2018)
Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P. Burgess, Matko Bosnjak, Murray Shanahan, Matthew Botvinick, Demis Hassabis, Alexander Lerchner
SCAN: Learning Hierarchical Compositional Visual Concepts. ICLR (Poster) (2018)
Vinícius Flores Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David P. Reichert, Timothy P. Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, Peter W. Battaglia
Relational Deep Reinforcement Learning. CoRR (2018)
Christos Kaplanis, Murray Shanahan, Claudia Clopath
Continual Reinforcement Learning with Complex Synapses. CoRR (2018)
Marta Garnelo, Dan Rosenbaum, Chris J. Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo J. Rezende, S. M. Ali Eslami
Conditional Neural Processes. CoRR (2018)
Nat Dilokthanakul, Murray Shanahan
Deep Reinforcement Learning with Risk-Seeking Exploration. SAB (2018)
Marta Garnelo, Dan Rosenbaum, Christopher Maddison, Tiago Ramalho, David Saxton, Murray Shanahan, Yee Whye Teh, Danilo Jimenez Rezende, S. M. Ali Eslami
Conditional Neural Processes. ICML (2018)
Ananya Kumar, S. M. Ali Eslami, Danilo J. Rezende, Marta Garnelo, Fabio Viola, Edward Lockhart, Murray Shanahan
Consistent Generative Query Networks. CoRR (2018)
Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. CoRR (2017)
Tycho M. S. Tax, Pedro A. M. Mediano, Murray Shanahan
The Partial Information Decomposition of Generative Neural Network Models. Entropy 19 (9) (2017)
Kyriacos Nikiforou, Pedro A. M. Mediano, Murray Shanahan
An Investigation of the Dynamical Transitions in Harmonically Driven Random Networks of Firing-Rate Neurons. Cogn. Comput. 9 (3) (2017)
Marta Garnelo, Kai Arulkumaran, Murray Shanahan
Towards Deep Symbolic Reinforcement Learning. CoRR (2016)
Nat Dilokthanakul, Pedro A. M. Mediano, Marta Garnelo, Matthew C. H. Lee, Hugh Salimbeni, Kai Arulkumaran, Murray Shanahan
Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders. CoRR (2016)
Kai Arulkumaran, Nat Dilokthanakul, Murray Shanahan, Anil Anthony Bharath
Classifying Options for Deep Reinforcement Learning. CoRR (2016)
David Bhowmik, Kyriacos Nikiforou, Murray Shanahan, Michail Maniadakis, Panos E. Trahanias
A reservoir computing model of episodic memory. IJCNN (2016)
Frantisek Vása, Murray Shanahan, Peter J. Hellyer, Gregory P. T. Scott, Joana Cabral, Robert Leech
Effects of lesions on synchrony and metastability in cortical networks. NeuroImage 118 (2015)
Filipe Peliz Pinto Teixeira, Murray Shanahan
Local and global criticality within oscillating networks of spiking neurons. IJCNN (2015)
Murray Shanahan
Ascribing Consciousness to Artificial Intelligence. CoRR (2015)
Zafeirios Fountas, Murray Shanahan
GPU-based fast parameter optimization for phenomenological spiking neural models. IJCNN (2015)
Zafeirios Fountas, Murray Shanahan
Phase offset between slow oscillatory cortical inputs influences competition in a model of the basal ganglia. IJCNN (2014)
Filipe Peliz Pinto Teixeira, Murray Shanahan
Does plasticity promote criticality? IJCNN (2014)
David Bhowmik, Murray Shanahan
STDP produces robust oscillatory architectures that exhibit precise collective synchronization. IJCNN (2013)
Zafeirios Fountas, Murray Shanahan
A Cognitive Neural Architecture as a Robot Controller. Living Machines (2013)
Andreas Fidjeland, David Gamez, Murray Shanahan, Edgars Lazdins
Three Tools for the Real-Time Simulation of Embodied Spiking Neural Networks Using GPUs. Neuroinformatics 11 (3) (2013)
Murray Shanahan, Verner P. Bingman, Toru Shimizu, Martin Wild, Onur Güntürkün
Large-scale network organization in the avian forebrain: a connectivity matrix and theoretical analysis. Frontiers Comput. Neurosci. 7 (2013)
David Bhowmik, Murray Shanahan
How well do oscillator models capture the behaviour of biological neurons? IJCNN (2012)
Mark Wildie, Murray Shanahan
Hierarchical clustering identifies hub nodes in a model of resting-state brain activity. IJCNN (2012)
Mark Wildie, Murray Shanahan
Establishing communication between neuronal populations through competitive entrainment. Frontiers Comput. Neurosci. 5 (2011)
Murray Shanahan
Serial from Parallel, Unity from Multiplicity: What Emerges from Global Workspace Architecture. BICA (2011)
Andreas Fidjeland, Murray Shanahan
Accelerated simulation of spiking neural networks using GPUs. IJCNN (2010)
Dustin Connor, Murray Shanahan
A computational model of a global neuronal workspace with stochastic connections. Neural Networks 23 (10) (2010)
Alexandros Bouganis, Murray Shanahan
Training a spiking neural network to control a 4-DoF robotic arm based on Spike Timing-Dependent Plasticity. IJCNN (2010)
Andreas Fidjeland, Etienne B. Roesch, Murray Shanahan, Wayne Luk
NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs. ASAP (2009)
Andreas Fidjeland, Murray Shanahan, Alexandros Bouganis
Object Detection for a Humanoid Robot Using a Probabilistic Global Workspace. ICVW (2008)
Murray Shanahan, Dustin Connor
Modeling the Neural Basis of Cognitive Integration and Consciousness. ALIFE (2008)
Alexandros Bouganis, Murray Shanahan
Flexible object recognition in cluttered scenes using relative point distribution models. ICPR (2008)
Dustin Connor, Murray Shanahan
A Simulated Global Neuronal Workspace with Stochastic Wiring. AAAI Fall Symposium: AI and Consciousness (2007)
Alexandros Bouganis, Murray Shanahan
A Vision-Based Intelligent System for Packing 2-D Irregular Shapes. IEEE Trans Autom. Sci. Eng. 4 (3) (2007)
Secil Ozen, Alexandros Bouganis, Murray Shanahan
A fast evaluation criterion for the recognition of occluded shapes. Robotics Auton. Syst. 55 (9) (2007)
Alexandros Bouganis, Murray Shanahan
On Packing 2D Irregular Shapes. ECAI (2006)
Georgios Sakellariou, Murray Shanahan
Leaf Classification Using Navigation-Based Skeletons. ECAI (2006)
Murray Shanahan
Perception as Abduction: Turning Sensor Data Into Meaningful Representation. Cogn. Sci. 29 (1) (2005)
Murray Shanahan
An attempt to formalise a non-trivial benchmark problem in common sense reasoning. Artif. Intell. 153 (1-2) (2004)
Murray Shanahan, David A. Randell
A Logic-Based Formulation of Active Visual Perception. KR (2004)
Jeremy Forth, Murray Shanahan
Indirect and Conditional Sensing in the Event Calculus. ECAI (2004)
Murray Shanahan, Mark Witkowski
Event Calculus Planning Through Satisfiability. J. Log. Comput. 14 (5) (2004)
Paulo E. Santos, Murray Shanahan
A Logic-based Algorithm for Image Sequence Interpretation and Anchoring. IJCAI (2003)
Paulo E. Santos, Murray Shanahan
Hypothesising Object Relations from Image Transitions. ECAI (2002)
Rob Miller, Murray Shanahan
Some Alternative Formulations of the Event Calculus. Computational Logic: Logic Programming and Beyond (2002)
Murray Shanahan
A Logical Account of Perception Incorporating Feedback and Expectation. KR (2002)
David A. Randell, Mark Witkowski, Murray Shanahan
From Images to Bodies: Modelling and Exploiting Spatial Occlusion and Motion Parallax. IJCAI (2001)
Murray Shanahan
Review: M. Shanahan, Solving the Frame Problem. Artif. Intell. 123 (1-2) (2000)
Murray Shanahan
An abductive event calculus planner. J. Log. Program. 44 (1-3) (2000)
Murray Shanahan, Mark Witkowski
High-Level Robot Control through Logic. ATAL (2000)
Murray Shanahan, Mark Witkowski
Robot Navigation and Map Building with the Event Calculus (abstract). ESCQARU (1999)
Murray Shanahan
The Ramification Problem in the Event Calculus. IJCAI (1999)
Rob Miller, Murray Shanahan
The Event Calculus in Classical Logic - Alternative Axiomatisations. Electron. Trans. Artif. Intell. 3 (A) (1999)
Murray Shanahan
A Logical Account of the Common Sense Informatic Situation for a Mobile Robot. Electron. Trans. Artif. Intell. 2 (1998)
Murray Shanahan
Noise, Non-Determinism and Spatial Uncertainty. AAAI/IAAI (1997)
Murray Shanahan
Event Calculus Planning Revisited. ECP (1997)
Rob Miller, Murray Shanahan
Reasoning about Discontinuities in the Event Calculus. KR (1996)

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Publication Activity (10 Years)

Top Topics

Top Venues

Murray Shanahan