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ORCIDMurray Shanahan
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- affiliation: Imperial College London, UK
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2020 – today
- 2024
[j24]Murray Shanahan:
Talking about Large Language Models. Commun. ACM 67(2): 68-79 (2024)- [c53]Nandi Schoots, Alex Jackson, Ali Kholmovia, Peter McBurney, Murray Shanahan:
The Propensity for Density in Feed-Forward Models. ECAI 2024: 2830-2837 - [i33]Murray Shanahan:
Simulacra as Conscious Exotica. CoRR abs/2402.12422 (2024) - [i32]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 abs/2404.15058 (2024) - [i31]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 abs/2404.16244 (2024) - 2023
- [j23]Murray Shanahan
, Kyle McDonell, Laria Reynolds:
Role play with large language models. Nat. 623(7987): 493-498 (2023) - [j22]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) - [c52]Antonia Creswell, Murray Shanahan, Irina Higgins:
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning. ICLR 2023 - [c51]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 - [i30]Murray Shanahan, Kyle McDonell, Laria Reynolds:
Role-Play with Large Language Models. CoRR abs/2305.16367 (2023) - [i29]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 abs/2307.01201 (2023) - [i28]Murray Shanahan, Catherine Clarke:
Evaluating Large Language Model Creativity from a Literary Perspective. CoRR abs/2312.03746 (2023) - [i27]Ole Jorgensen, Dylan Cope, Nandi Schoots, Murray Shanahan:
Improving Activation Steering in Language Models with Mean-Centring. CoRR abs/2312.03813 (2023) - 2022
- [j21]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): 1501-1544 (2022) - [c50]Borja G. León, Murray Shanahan, Francesco Belardinelli:
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications. ICLR 2022 - [c49]Murray Shanahan, Melanie Mitchell:
Abstraction for Deep Reinforcement Learning. IJCAI 2022: 5588-5596 - [i26]Murray Shanahan, Melanie Mitchell:
Abstraction for Deep Reinforcement Learning. CoRR abs/2202.05839 (2022) - [i25]Antonia Creswell, Murray Shanahan, Irina Higgins:
Selection-Inference: Exploiting Large Language Models for Interpretable Logical Reasoning. CoRR abs/2205.09712 (2022) - [i24]Alex F. Spies, Alessandra Russo, Murray Shanahan:
Sparse Relational Reasoning with Object-Centric Representations. CoRR abs/2207.07512 (2022) - [i23]Antonia Creswell, Murray Shanahan:
Faithful Reasoning Using Large Language Models. CoRR abs/2208.14271 (2022) - [i22]Murray Shanahan:
Talking About Large Language Models. CoRR abs/2212.03551 (2022) - 2021
- [c48]Antonia Creswell, Rishabh Kabra, Christopher P. Burgess, Murray Shanahan:
Unsupervised Object-Based Transition Models For 3D Partially Observable Environments. NeurIPS 2021: 27344-27355 - [i21]Antonia Creswell, Rishabh Kabra, Chris Burgess, Murray Shanahan:
Unsupervised Object-Based Transition Models for 3D Partially Observable Environments. CoRR abs/2103.04693 (2021) - [i20]Murray Shanahan, Christos Kaplanis, Jovana Mitrovic:
Encoders and Ensembles for Task-Free Continual Learning. CoRR abs/2105.13327 (2021) - [i19]Borja G. León, Murray Shanahan, Francesco Belardinelli:
In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications. CoRR abs/2110.09461 (2021) - [i18]Wilka Carvalho, Andrew K. Lampinen, Kyriacos Nikiforou, Felix Hill, Murray Shanahan:
Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning. CoRR abs/2112.08369 (2021) - 2020
- [c47]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: 6972-6986 - [c46]Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David G. T. Barrett, Marta Garnelo:
An Explicitly Relational Neural Network Architecture. ICML 2020: 8593-8603 - [i17]Christos Kaplanis, Claudia Clopath, Murray Shanahan:
Continual Reinforcement Learning with Multi-Timescale Replay. CoRR abs/2004.07530 (2020) - [i16]Daniel Pace, Alessandra Russo, Murray Shanahan:
Learning Diverse Representations for Fast Adaptation to Distribution Shift. CoRR abs/2006.07119 (2020) - [i15]Borja G. León, Murray Shanahan, Francesco Belardinelli:
Systematic Generalisation through Task Temporal Logic and Deep Reinforcement Learning. CoRR abs/2006.08767 (2020) - [i14]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 abs/2006.16981 (2020) - [i13]Antonia Creswell, Kyriacos Nikiforou, Oriol Vinyals, Andre Saraiva, Rishabh Kabra, Loic Matthey, Chris Burgess, Malcolm Reynolds, Richard Tanburn, Marta Garnelo, Murray Shanahan:
AlignNet: Unsupervised Entity Alignment. CoRR abs/2007.08973 (2020)
2010 – 2019
- 2019
- [j20]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): 3409-3418 (2019) - [c45]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 M. Botvinick, Oriol Vinyals, Peter W. Battaglia:
Deep reinforcement learning with relational inductive biases. ICLR (Poster) 2019 - [c44]Christos Kaplanis, Murray Shanahan, Claudia Clopath:
Policy Consolidation for Continual Reinforcement Learning. ICML 2019: 3242-3251 - [c43]Matthew Crosby, Benjamin Beyret, Murray Shanahan, José Hernández-Orallo, Lucy Cheke, Marta Halina:
The Animal-AI Testbed and Competition. NeurIPS (Competition and Demos) 2019: 164-176 - [i12]Christos Kaplanis, Murray Shanahan, Claudia Clopath:
Policy Consolidation for Continual Reinforcement Learning. CoRR abs/1902.00255 (2019) - [i11]Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David Barrett, Marta Garnelo:
An Explicitly Relational Neural Network Architecture. CoRR abs/1905.10307 (2019) - [i10]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 abs/1909.07483 (2019) - 2018
- [c42]Irina Higgins, Nicolas Sonnerat, Loic Matthey, Arka Pal, Christopher P. Burgess, Matko Bosnjak, Murray Shanahan, Matthew M. Botvinick, Demis Hassabis, Alexander Lerchner:
SCAN: Learning Hierarchical Compositional Visual Concepts. ICLR (Poster) 2018 - [c41]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: 1690-1699 - [c40]Christos Kaplanis, Murray Shanahan, Claudia Clopath:
Continual Reinforcement Learning with Complex Synapses. ICML 2018: 2502-2511 - [c39]Nat Dilokthanakul, Murray Shanahan:
Deep Reinforcement Learning with Risk-Seeking Exploration. SAB 2018: 201-211 - [i9]Christos Kaplanis, Murray Shanahan, Claudia Clopath:
Continual Reinforcement Learning with Complex Synapses. CoRR abs/1802.07239 (2018) - [i8]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 M. Botvinick, Oriol Vinyals, Peter W. Battaglia:
Relational Deep Reinforcement Learning. CoRR abs/1806.01830 (2018) - [i7]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 abs/1807.01613 (2018) - [i6]Ananya Kumar, S. M. Ali Eslami, Danilo J. Rezende, Marta Garnelo, Fabio Viola, Edward Lockhart, Murray Shanahan:
Consistent Generative Query Networks. CoRR abs/1807.02033 (2018) - 2017
- [j19]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): 351-363 (2017) - [j18]Tycho M. S. Tax, Pedro A. M. Mediano, Murray Shanahan:
The Partial Information Decomposition of Generative Neural Network Models. Entropy 19(9): 474 (2017) - [i5]Nat Dilokthanakul, Christos Kaplanis, Nick Pawlowski, Murray Shanahan:
Feature Control as Intrinsic Motivation for Hierarchical Reinforcement Learning. CoRR abs/1705.06769 (2017) - 2016
- [c38]David Bhowmik, Kyriacos Nikiforou, Murray Shanahan, Michail Maniadakis, Panos E. Trahanias:
A reservoir computing model of episodic memory. IJCNN 2016: 5202-5209 - [i4]Kai Arulkumaran, Nat Dilokthanakul, Murray Shanahan, Anil Anthony Bharath:
Classifying Options for Deep Reinforcement Learning. CoRR abs/1604.08153 (2016) - [i3]Marta Garnelo, Kai Arulkumaran, Murray Shanahan:
Towards Deep Symbolic Reinforcement Learning. CoRR abs/1609.05518 (2016) - [i2]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 abs/1611.02648 (2016) - 2015
- [j17]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: 456-467 (2015) - [c37]Zafeirios Fountas, Murray Shanahan:
GPU-based fast parameter optimization for phenomenological spiking neural models. IJCNN 2015: 1-8 - [c36]Filipe Peliz Pinto Teixeira, Murray Shanahan:
Local and global criticality within oscillating networks of spiking neurons. IJCNN 2015: 1-7 - [i1]Murray Shanahan:
Ascribing Consciousness to Artificial Intelligence. CoRR abs/1504.05696 (2015) - 2014
- [c35]Filipe Peliz Pinto Teixeira, Murray Shanahan:
Does plasticity promote criticality? IJCNN 2014: 2383-2390 - [c34]Zafeirios Fountas, Murray Shanahan:
Phase offset between slow oscillatory cortical inputs influences competition in a model of the basal ganglia. IJCNN 2014: 2407-2414 - 2013
- [j16]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: 89 (2013) - [j15]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): 267-290 (2013) - [c33]David Bhowmik, Murray Shanahan:
STDP produces robust oscillatory architectures that exhibit precise collective synchronization. IJCNN 2013: 1-8 - [c32]Zafeirios Fountas, Murray Shanahan:
A Cognitive Neural Architecture as a Robot Controller. Living Machines 2013: 371-373 - 2012
- [c31]David Bhowmik, Murray Shanahan:
How well do oscillator models capture the behaviour of biological neurons? IJCNN 2012: 1-8 - [c30]Mark Wildie, Murray Shanahan:
Hierarchical clustering identifies hub nodes in a model of resting-state brain activity. IJCNN 2012: 1-6 - 2011
- [j14]Mark Wildie, Murray Shanahan:
Establishing communication between neuronal populations through competitive entrainment. Frontiers Comput. Neurosci. 5: 62 (2011) - [c29]Murray Shanahan:
Serial from Parallel, Unity from Multiplicity: What Emerges from Global Workspace Architecture. BICA 2011: 343 - 2010
- [j13]Dustin Connor, Murray Shanahan:
A computational model of a global neuronal workspace with stochastic connections. Neural Networks 23(10): 1139-1154 (2010) - [c28]Alexandros Bouganis, Murray Shanahan:
Training a spiking neural network to control a 4-DoF robotic arm based on Spike Timing-Dependent Plasticity. IJCNN 2010: 1-8 - [c27]Andreas Fidjeland, Murray Shanahan:
Accelerated simulation of spiking neural networks using GPUs. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [c26]Andreas Fidjeland, Etienne B. Roesch, Murray Shanahan, Wayne Luk:
NeMo: A Platform for Neural Modelling of Spiking Neurons Using GPUs. ASAP 2009: 137-144 - 2008
- [c25]Murray Shanahan, Dustin Connor:
Modeling the Neural Basis of Cognitive Integration and Consciousness. ALIFE 2008: 553-560 - [c24]Alexandros Bouganis, Murray Shanahan:
Flexible object recognition in cluttered scenes using relative point distribution models. ICPR 2008: 1-5 - [c23]Andreas Fidjeland, Murray Shanahan, Alexandros Bouganis:
Object Detection for a Humanoid Robot Using a Probabilistic Global Workspace. ICVW 2008: 135-148 - 2007
- [j12]Secil Ozen, Alexandros Bouganis, Murray Shanahan:
A fast evaluation criterion for the recognition of occluded shapes. Robotics Auton. Syst. 55(9): 741-749 (2007) - [j11]Alexandros Bouganis, Murray Shanahan:
A Vision-Based Intelligent System for Packing 2-D Irregular Shapes. IEEE Trans Autom. Sci. Eng. 4(3): 382-394 (2007) - [c22]Dustin Connor, Murray Shanahan:
A Simulated Global Neuronal Workspace with Stochastic Wiring. AAAI Fall Symposium: AI and Consciousness 2007: 43-48 - 2006
- [c21]Alexandros Bouganis, Murray Shanahan:
On Packing 2D Irregular Shapes. ECAI 2006: 853-854 - [c20]Georgios Sakellariou, Murray Shanahan:
Leaf Classification Using Navigation-Based Skeletons. ECAI 2006: 859-860 - 2005
- [j10]Murray Shanahan:
Perception as Abduction: Turning Sensor Data Into Meaningful Representation. Cogn. Sci. 29(1): 103-134 (2005) - 2004
- [j9]Murray Shanahan:
An attempt to formalise a non-trivial benchmark problem in common sense reasoning. Artif. Intell. 153(1-2): 141-165 (2004) - [j8]Murray Shanahan, Mark Witkowski:
Event Calculus Planning Through Satisfiability. J. Log. Comput. 14(5): 731-745 (2004) - [c19]Jeremy Forth, Murray Shanahan:
Indirect and Conditional Sensing in the Event Calculus. ECAI 2004: 900-904 - [c18]Murray Shanahan, David A. Randell:
A Logic-Based Formulation of Active Visual Perception. KR 2004: 64-72 - 2003
- [c17]Paulo E. Santos, Murray Shanahan:
A Logic-based Algorithm for Image Sequence Interpretation and Anchoring. IJCAI 2003: 1408- - 2002
- [c16]Rob Miller, Murray Shanahan:
Some Alternative Formulations of the Event Calculus. Computational Logic: Logic Programming and Beyond 2002: 452-490 - [c15]Paulo E. Santos, Murray Shanahan:
Hypothesising Object Relations from Image Transitions. ECAI 2002: 292-296 - [c14]Murray Shanahan:
A Logical Account of Perception Incorporating Feedback and Expectation. KR 2002: 3-13 - 2001
- [c13]David A. Randell, Mark Witkowski, Murray Shanahan:
From Images to Bodies: Modelling and Exploiting Spatial Occlusion and Motion Parallax. IJCAI 2001: 57-66 - 2000
- [j7]Murray Shanahan:
Review: M. Shanahan, Solving the Frame Problem. Artif. Intell. 123(1-2): 275 (2000) - [j6]Murray Shanahan:
An abductive event calculus planner. J. Log. Program. 44(1-3): 207-240 (2000) - [c12]Murray Shanahan, Mark Witkowski:
High-Level Robot Control through Logic. ATAL 2000: 104-121
1990 – 1999
- 1999
- [j5]Rob Miller, Murray Shanahan:
The Event Calculus in Classical Logic - Alternative Axiomatisations. Electron. Trans. Artif. Intell. 3(A): 77-105 (1999) - [c11]Murray Shanahan, Mark Witkowski:
Robot Navigation and Map Building with the Event Calculus (abstract). ESCQARU 1999: 362 - [c10]Murray Shanahan:
The Ramification Problem in the Event Calculus. IJCAI 1999: 140-146 - [p1]Murray Shanahan:
The Event Calculus Explained. Artificial Intelligence Today 1999: 409-430 - 1998
- [j4]Murray Shanahan:
A Logical Account of the Common Sense Informatic Situation for a Mobile Robot. Electron. Trans. Artif. Intell. 2: 69-104 (1998) - 1997
- [b2]Murray Shanahan:
Solving the frame problem - a mathematical investigation of the common sense law of inertia. MIT Press 1997, ISBN 978-0-262-19384-9, pp. I-XXXIV, 1-407 - [c9]Murray Shanahan:
Noise, Non-Determinism and Spatial Uncertainty. AAAI/IAAI 1997: 153-158 - [c8]Murray Shanahan:
Event Calculus Planning Revisited. ECP 1997: 390-402 - 1996
- [c7]Murray Shanahan:
Noise and the Common Sense Informatic Situation for a Mobile Robot. AAAI/IAAI, Vol. 2 1996: 1098-1103 - [c6]Murray Shanahan:
Robotics and the Common Sense Informatic Situation. ECAI 1996: 684-688 - [c5]Rob Miller, Murray Shanahan:
Reasoning about Discontinuities in the Event Calculus. KR 1996: 63-74 - 1995
- [j3]Murray Shanahan:
Default Reasoning about Spatial Occupancy. Artif. Intell. 74(1): 147-163 (1995) - [j2]Murray Shanahan:
A Circumscriptive Calculus of Events. Artif. Intell. 77(2): 249-284 (1995) - 1994
- [j1]Rob Miller, Murray Shanahan:
Narratives in the Situation Calculus. J. Log. Comput. 4(5): 513-530 (1994) - 1993
- [c4]Murray Shanahan:
Explanation in the Situation Calculus. IJCAI 1993: 160-165 - 1990
- [c3]Murray Shanahan:
Representing Continuous Change in the Event Calculus. ECAI 1990: 598-603
1980 – 1989
- 1989
- [b1]Murray Shanahan, Richard Southwick:
Search, inference and dependencies in artificial intelligence. Ellis Horwood Series in artificial intelligence, Ellis Horwood 1989, ISBN 978-0-7458-0488-0, pp. 1-140 - [c2]Murray Shanahan:
Prediction is Deduction but Explanation is Abduction. IJCAI 1989: 1055-1060 - 1987
- [c1]Murray Shanahan:
An Incremental Theorem Prover. IJCAI 1987: 987-989
Coauthor Index
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