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Joseph Modayil
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2020 – today
- 2023
- [j8]Matthew Koichi Grimes, Joseph Modayil, Piotr W. Mirowski, Dushyant Rao, Raia Hadsell:
Learning to Look by Self-Prediction. Trans. Mach. Learn. Res. 2023 (2023) - [c25]Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado:
Loss of Plasticity in Continual Deep Reinforcement Learning. CoLLAs 2023: 620-636 - [i14]Zaheer Abbas, Rosie Zhao, Joseph Modayil, Adam White, Marlos C. Machado:
Loss of Plasticity in Continual Deep Reinforcement Learning. CoRR abs/2303.07507 (2023) - [i13]Joseph Modayil, Zaheer Abbas:
Towards model-free RL algorithms that scale well with unstructured data. CoRR abs/2311.02215 (2023) - 2022
- [i12]Andrew Butcher, Michael Bradley Johanson, Elnaz Davoodi, Dylan J. A. Brenneis, Leslie Acker, Adam S. R. Parker, Adam White, Joseph Modayil, Patrick M. Pilarski:
Pavlovian Signalling with General Value Functions in Agent-Agent Temporal Decision Making. CoRR abs/2201.03709 (2022) - [i11]Patrick M. Pilarski, Andrew Butcher, Elnaz Davoodi, Michael Bradley Johanson, Dylan J. A. Brenneis, Adam S. R. Parker, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White:
The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents. CoRR abs/2203.09498 (2022) - 2021
- [i10]John D. Martin, Joseph Modayil:
Adapting the Function Approximation Architecture in Online Reinforcement Learning. CoRR abs/2106.09776 (2021) - [i9]Dylan J. A. Brenneis, Adam S. R. Parker, Michael Bradley Johanson, Andrew Butcher, Elnaz Davoodi, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White, Patrick M. Pilarski:
Assessing Human Interaction in Virtual Reality With Continually Learning Prediction Agents Based on Reinforcement Learning Algorithms: A Pilot Study. CoRR abs/2112.07774 (2021)
2010 – 2019
- 2019
- [i8]Tom Schaul, Diana Borsa, Joseph Modayil, Razvan Pascanu:
Ray Interference: a Source of Plateaus in Deep Reinforcement Learning. CoRR abs/1904.11455 (2019) - [i7]Matteo Hessel, Hado van Hasselt, Joseph Modayil, David Silver:
On Inductive Biases in Deep Reinforcement Learning. CoRR abs/1907.02908 (2019) - 2018
- [j7]Andrea Banino, Caswell Barry
, Benigno Uria, Charles Blundell, Timothy P. Lillicrap, Piotr Mirowski, Alexander Pritzel, Martin J. Chadwick, Thomas Degris, Joseph Modayil, Greg Wayne, Hubert Soyer, Fabio Viola, Brian Zhang, Ross Goroshin, Neil C. Rabinowitz
, Razvan Pascanu, Charlie Beattie
, Stig Petersen, Amir Sadik, Stephen Gaffney, Helen King, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Dharshan Kumaran:
Vector-based navigation using grid-like representations in artificial agents. Nat. 557(7705): 429-433 (2018) - [c24]Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver:
Rainbow: Combining Improvements in Deep Reinforcement Learning. AAAI 2018: 3215-3222 - [i6]Tom Schaul, Hado van Hasselt, Joseph Modayil, Martha White, Adam White, Pierre-Luc Bacon, Jean Harb, Shibl Mourad, Marc G. Bellemare, Doina Precup:
The Barbados 2018 List of Open Issues in Continual Learning. CoRR abs/1811.07004 (2018) - [i5]Hado van Hasselt, Yotam Doron, Florian Strub, Matteo Hessel, Nicolas Sonnerat, Joseph Modayil:
Deep Reinforcement Learning and the Deadly Triad. CoRR abs/1812.02648 (2018) - 2017
- [c23]Zhongwen Xu, Joseph Modayil, Hado van Hasselt, André Barreto, David Silver, Tom Schaul:
Natural Value Approximators: Learning when to Trust Past Estimates. NIPS 2017: 2120-2128 - [i4]Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Daniel Horgan, Bilal Piot, Mohammad Gheshlaghi Azar, David Silver:
Rainbow: Combining Improvements in Deep Reinforcement Learning. CoRR abs/1710.02298 (2017) - [i3]Matthew M. Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis:
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR abs/1711.08378 (2017) - 2014
- [j6]Joseph Modayil, Adam White, Richard S. Sutton:
Multi-timescale nexting in a reinforcement learning robot. Adapt. Behav. 22(2): 146-160 (2014) - [c22]Hengshuai Yao, Csaba Szepesvári, Richard S. Sutton, Joseph Modayil, Shalabh Bhatnagar:
Universal Option Models. NIPS 2014: 990-998 - 2013
- [c21]Joseph Modayil:
Two Perspectives on Learning Rich Representations from Robot Experience. AAAI Workshop: Learning Rich Representations from Low-Level Sensors 2013 - 2012
- [j5]Noa Agmon, Vikas Agrawal, David W. Aha, Yiannis Aloimonos, Donagh Buckley, Prashant Doshi, Christopher W. Geib, Floriana Grasso
, Nancy L. Green, Benjamin Johnston, Burt Kaliski, Christopher Kiekintveld, Edith Law, Henry Lieberman, Ole J. Mengshoel, Ted Metzler, Joseph Modayil, Douglas W. Oard
, Nilufer Onder, Barry O'Sullivan, Katerina Pastra
, Doina Precup, Sowmya Ramachandran, Chris Reed, Sanem Sariel Talay
, Ted Selker, Lokendra Shastri, Stephen F. Smith, Satinder Singh, Siddharth Srivastava, Gita Sukthankar, David C. Uthus, Mary-Anne Williams:
Reports of the AAAI 2011 Conference Workshops. AI Mag. 33(1): 57-70 (2012) - [c20]Thomas Degris, Joseph Modayil:
Scaling-up Knowledge for a Cognizant Robot. AAAI Spring Symposium: Designing Intelligent Robots 2012 - [c19]Adam White, Joseph Modayil, Richard S. Sutton:
Scaling life-long off-policy learning. ICDL-EPIROB 2012: 1-6 - [c18]Joseph Modayil, Adam White, Richard S. Sutton:
Multi-timescale Nexting in a Reinforcement Learning Robot. SAB 2012: 299-309 - [c17]Joseph Modayil, Adam White, Patrick M. Pilarski
, Richard S. Sutton:
Acquiring a broad range of empirical knowledge in real time by temporal-difference learning. SMC 2012: 1903-1910 - [i2]Adam White, Joseph Modayil, Richard S. Sutton:
Scaling Life-long Off-policy Learning. CoRR abs/1206.6262 (2012) - 2011
- [c16]Richard S. Sutton, Joseph Modayil, Michael Delp, Thomas Degris, Patrick M. Pilarski, Adam White, Doina Precup:
Horde: a scalable real-time architecture for learning knowledge from unsupervised sensorimotor interaction. AAMAS 2011: 761-768 - [i1]Joseph Modayil, Adam White, Richard S. Sutton:
Multi-timescale Nexting in a Reinforcement Learning Robot. CoRR abs/1112.1133 (2011) - 2010
- [j4]Patrick Beeson, Joseph Modayil, Benjamin Kuipers:
Factoring the Mapping Problem: Mobile Robot Map-building in the Hybrid Spatial Semantic Hierarchy. Int. J. Robotics Res. 29(4): 428-459 (2010) - [c15]Joseph Modayil:
Learning Grounded Communicative Intent from Human-Robot Dialog. AAAI Fall Symposium: Dialog with Robots 2010 - [c14]Joseph Modayil:
Discovering sensor space: Constructing spatial embeddings that explain sensor correlations. ICDL 2010: 120-125 - [c13]Yasin Abbasi-Yadkori, Joseph Modayil, Csaba Szepesvári:
Extending rapidly-exploring random trees for asymptotically optimal anytime motion planning. IROS 2010: 127-132
2000 – 2009
- 2008
- [j3]Joseph Modayil, Benjamin Kuipers:
The initial development of object knowledge by a learning robot. Robotics Auton. Syst. 56(11): 879-890 (2008) - [c12]Joseph Modayil, Richard Levinson, Craig Harman, David Halper, Henry A. Kautz:
Integrating Sensing and Cueing for More Effective Activity Reminders. AAAI Fall Symposium: AI in Eldercare: New Solutions to Old Problems 2008: 60-66 - [c11]Joseph Modayil, Tongxin Bai, Henry A. Kautz
:
Improving the recognition of interleaved activities. UbiComp 2008: 40-43 - 2007
- [c10]Joseph Modayil, Benjamin Kuipers:
Autonomous Development of a Grounded Object Ontology by a Learning Robot. AAAI 2007: 1095-1101 - [c9]Patrick Beeson, Matt MacMahon, Joseph Modayil, Aniket Murarka, Benjamin Kuipers, Brian Stankiewicz:
Integrating Multiple Representations of Spatial Knowledge for Mapping, Navigation, and Communication. AAAI Spring Symposium: Interaction Challenges for Intelligent Assistants 2007: 1-9 - [c8]Joseph Modayil, Benjamin Kuipers:
Where Do Actions Come From? Autonomous Robot Learning of Objects and Actions. AAAI Spring Symposium: Control Mechanisms for Spatial Knowledge Processing in Cognitive / Intelligent Systems 2007: 41-46 - [c7]Patrick Beeson, Matt MacMahon, Joseph Modayil, Aniket Murarka, Benjamin Kuipers, Brian Stankiewicz:
Integrating Multiple Representations of Spatial Knowledge for Mapping, Navigation, and Communication. Interaction Challenges for Intelligent Assistants 2007: 1-9 - 2006
- [j2]Benjamin Kuipers, Patrick Beeson, Joseph Modayil, Jefferson Provost:
Bootstrap learning of foundational representations. Connect. Sci. 18(2): 145-158 (2006) - [c6]Aniket Murarka, Joseph Modayil, Benjamin Kuipers:
Building Local Safety Maps for a Wheelchair Robot using Vision and Lasers. CRV 2006: 25 - [c5]Joseph Modayil, Benjamin Kuipers:
Autonomous Shape Model Learning for Object Localization and Recognition. ICRA 2006: 2991-2996 - 2004
- [c4]Benjamin Kuipers, Joseph Modayil, Patrick Beeson, Matt MacMahon, Francesco Savelli:
Local Metrical and Global Topological Maps in the Hybrid Spatial Semantic Hierarchy. ICRA 2004: 4845-4851 - [c3]Joseph Modayil, Benjamin Kuipers:
Bootstrap learning for object discovery. IROS 2004: 742-747 - [c2]Joseph Modayil, Patrick Beeson, Benjamin Kuipers:
Using the topological skeleton for scalable global metrical map-building. IROS 2004: 1530-1536
1990 – 1999
- 1998
- [j1]Joseph Modayil, Howard Cheng, Xiaobo Li:
An improved piecewise approximation algorithm for image compression. Pattern Recognit. 31(8): 1179-1190 (1998) - 1997
- [c1]Joseph Modayil, Howard Cheng, Xiaobo Li:
Experiments in Simple One-Dimensional Lossy Image Compression Schemes. ICMCS 1997: 614-615
Coauthor Index
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last updated on 2024-04-25 05:55 CEST by the dblp team
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