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Pedro A. Ortega
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2020 – today
- 2023
- [c18]Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Chris Cundy, Marcus Hutter, Shane Legg, Joel Veness, Pedro A. Ortega:
Neural Networks and the Chomsky Hierarchy. ICLR 2023 - 2022
- [j10]Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega:
Your Policy Regularizer is Secretly an Adversary. Trans. Mach. Learn. Res. 2022 (2022) - [i36]Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega:
Your Policy Regularizer is Secretly an Adversary. CoRR abs/2203.12592 (2022) - [i35]Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega:
Neural Networks and the Chomsky Hierarchy. CoRR abs/2207.02098 (2022) - [i34]Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega:
Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR abs/2209.15618 (2022) - 2021
- [c17]Tom Everitt, Ryan Carey, Eric D. Langlois, Pedro A. Ortega, Shane Legg:
Agent Incentives: A Causal Perspective. AAAI 2021: 11487-11495 - [c16]Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls:
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. ICML 2021: 8525-8535 - [i33]Tom Everitt, Ryan Carey, Eric D. Langlois, Pedro A. Ortega, Shane Legg:
Agent Incentives: A Causal Perspective. CoRR abs/2102.01685 (2021) - [i32]Grégoire Delétang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega:
Causal Analysis of Agent Behavior for AI Safety. CoRR abs/2103.03938 (2021) - [i31]Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg:
Shaking the foundations: delusions in sequence models for interaction and control. CoRR abs/2110.10819 (2021) - [i30]Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega:
Model-Free Risk-Sensitive Reinforcement Learning. CoRR abs/2111.02907 (2021) - 2020
- [c15]Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega:
Meta-trained agents implement Bayes-optimal agents. NeurIPS 2020 - [i29]Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls:
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. CoRR abs/2002.08456 (2020) - [i28]Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl J. Friston, Nicolas Heess:
Action and Perception as Divergence Minimization. CoRR abs/2009.01791 (2020) - [i27]Vladimir Mikulik, Grégoire Delétang, Tom McGrath, Tim Genewein, Miljan Martic, Shane Legg, Pedro A. Ortega:
Meta-trained agents implement Bayes-optimal agents. CoRR abs/2010.11223 (2020) - [i26]Tim Genewein, Tom McGrath, Grégoire Delétang, Vladimir Mikulik, Miljan Martic, Shane Legg, Pedro A. Ortega:
Algorithms for Causal Reasoning in Probability Trees. CoRR abs/2010.12237 (2020)
2010 – 2019
- 2019
- [j9]Kanghoon Lee, Geon-hyeong Kim, Pedro A. Ortega, Daniel D. Lee, Kee-Eung Kim:
Bayesian optimistic Kullback-Leibler exploration. Mach. Learn. 108(5): 765-783 (2019) - [c14]Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas:
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning. ICML 2019: 3040-3049 - [i25]Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson:
Causal Reasoning from Meta-reinforcement Learning. CoRR abs/1901.08162 (2019) - [i24]Tom Everitt, Pedro A. Ortega, Elizabeth Barnes, Shane Legg:
Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings. CoRR abs/1902.09980 (2019) - [i23]Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew M. Botvinick, Shane Legg:
Meta-learning of Sequential Strategies. CoRR abs/1905.03030 (2019) - [i22]Jan Humplik, Alexandre Galashov, Leonard Hasenclever, Pedro A. Ortega, Yee Whye Teh, Nicolas Heess:
Meta reinforcement learning as task inference. CoRR abs/1905.06424 (2019) - 2018
- [i21]Pedro A. Ortega, Shane Legg:
Modeling Friends and Foes. CoRR abs/1807.00196 (2018) - [i20]Natasha Jaques, Angeliki Lazaridou, Edward Hughes, Çaglar Gülçehre, Pedro A. Ortega, DJ Strouse, Joel Z. Leibo, Nando de Freitas:
Intrinsic Social Motivation via Causal Influence in Multi-Agent RL. CoRR abs/1810.08647 (2018) - 2017
- [i19]Jan Leike, Miljan Martic, Victoria Krakovna, Pedro A. Ortega, Tom Everitt, Andrew Lefrancq, Laurent Orseau, Shane Legg:
AI Safety Gridworlds. CoRR abs/1711.09883 (2017) - 2016
- [c13]Teakgyu Hong, Jongmin Lee, Kee-Eung Kim, Pedro A. Ortega, Daniel D. Lee:
Bayesian Reinforcement Learning with Behavioral Feedback. IJCAI 2016: 1571-1577 - [c12]Pedro A. Ortega, Alan A. Stocker:
Human Decision-Making under Limited Time. NIPS 2016: 100-108 - [i18]Pedro A. Ortega, Naftali Tishby:
Memory controls time perception and intertemporal choices. CoRR abs/1604.05129 (2016) - [i17]Pedro A. Ortega, Alan A. Stocker:
Human Decision-Making under Limited Time. CoRR abs/1610.01698 (2016) - 2015
- [j8]Pedro A. Ortega:
Subjectivity, Bayesianism, and causality. Pattern Recognit. Lett. 64: 63-70 (2015) - [c11]Pedro A. Ortega, Kee-Eung Kim, Daniel D. Lee:
Reactive bandits with attitude. AISTATS 2015 - [c10]Pedro A. Ortega, Daniel D. Lee, Alan A. Stocker:
Causal reasoning in a prediction task with hidden causes. CogSci 2015 - [c9]Pedro A. Ortega, Koby Crammer, Daniel D. Lee:
Belief flows for robust online learning. ITA 2015: 70-77 - [i16]Pedro A. Ortega, Koby Crammer, Daniel D. Lee:
Belief Flows of Robust Online Learning. CoRR abs/1505.07067 (2015) - [i15]Pedro A. Ortega, Daniel A. Braun, Justin Dyer, Kee-Eung Kim, Naftali Tishby:
Information-Theoretic Bounded Rationality. CoRR abs/1512.06789 (2015) - 2014
- [j7]Pedro A. Ortega, Daniel A. Braun:
Generalized Thompson sampling for sequential decision-making and causal inference. Complex Adapt. Syst. Model. 2: 2 (2014) - [j6]Pedro A. Ortega, Daniel A. Braun:
Erratum to: Generalized Thompson sampling for sequential decision-making and causal inference. Complex Adapt. Syst. Model. 2: 4 (2014) - [j5]Daniel A. Braun, Pedro A. Ortega:
Information-Theoretic Bounded Rationality and ε-Optimality. Entropy 16(8): 4662-4676 (2014) - [c8]Pedro A. Ortega, Daniel D. Lee:
An Adversarial Interpretation of Information-Theoretic Bounded Rationality. AAAI 2014: 2483-2489 - [c7]Pedro A. Ortega, Daniel A. Braun, Naftali Tishby:
Monte Carlo methods for exact & efficient solution of the generalized optimality equations. ICRA 2014: 4322-4327 - [i14]Pedro A. Ortega, Daniel D. Lee:
An Adversarial Interpretation of Information-Theoretic Bounded Rationality. CoRR abs/1404.5668 (2014) - [i13]Pedro A. Ortega:
Subjectivity, Bayesianism, and Causality. CoRR abs/1407.4139 (2014) - 2013
- [j4]David Balduzzi, Pedro A. Ortega, Michel Besserve:
Metabolic Cost as an Organizing Principle for Cooperative Learning. Adv. Complex Syst. 16(2-3) (2013) - [i12]Pedro A. Ortega, Daniel A. Braun:
Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference. CoRR abs/1303.4431 (2013) - 2012
- [j3]Jordi Grau-Moya, Pedro A. Ortega, Daniel A. Braun:
Risk-Sensitivity in Bayesian Sensorimotor Integration. PLoS Comput. Biol. 8(9) (2012) - [c6]Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun:
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function. NIPS 2012: 3014-3022 - [i11]David Balduzzi, Pedro A. Ortega, Michel Besserve:
Metabolic cost as an organizing principle for cooperative learning. CoRR abs/1202.4482 (2012) - [i10]Pedro A. Ortega, Daniel A. Braun:
Free Energy and the Generalized Optimality Equations for Sequential Decision Making. CoRR abs/1205.3997 (2012) - [i9]Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun:
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function. CoRR abs/1206.1898 (2012) - 2011
- [c5]Daniel A. Braun, Pedro A. Ortega, Evangelos A. Theodorou, Stefan Schaal:
Path integral control and bounded rationality. ADPRL 2011: 202-209 - [c4]Daniel Alexander Braun, Pedro Alejandro Ortega:
Information, Utility and Bounded Rationality. AGI 2011: 269-274 - [c3]Pedro Alejandro Ortega, Daniel Alexander Braun, Simon J. Godsill:
Reinforcement Learning and the Bayesian Control Rule. AGI 2011: 281-285 - [i8]Pedro A. Ortega, Daniel A. Braun:
Information, Utility & Bounded Rationality. CoRR abs/1107.5766 (2011) - [i7]Pedro A. Ortega:
Bayesian Causal Induction. CoRR abs/1111.0708 (2011) - 2010
- [j2]Pedro A. Ortega, Daniel A. Braun:
A Minimum Relative Entropy Principle for Learning and Acting. J. Artif. Intell. Res. 38: 475-511 (2010) - [c2]Daniel A. Braun, Pedro A. Ortega:
A Minimum Relative Entropy Principle for Adaptive Control in Linear Quadratic Regulators. ICINCO (3) 2010: 103-108 - [i6]Pedro A. Ortega, Daniel A. Braun:
A Minimum Relative Entropy Controller for Undiscounted Markov Decision Processes. CoRR abs/1002.1480 (2010) - [i5]Pedro A. Ortega, Daniel A. Braun:
Convergence of Bayesian Control Rule. CoRR abs/1002.3086 (2010) - [i4]Pedro A. Ortega, Daniel A. Braun:
An axiomatic formalization of bounded rationality based on a utility-information equivalence. CoRR abs/1007.0940 (2010)
2000 – 2009
- 2009
- [j1]Daniel A. Braun, Pedro A. Ortega, Daniel M. Wolpert:
Nash Equilibria in Multi-Agent Motor Interactions. PLoS Comput. Biol. 5(8) (2009) - [i3]Pedro A. Ortega, Daniel A. Braun:
A Bayesian Rule for Adaptive Control based on Causal Interventions. CoRR abs/0911.5104 (2009) - [i2]Pedro A. Ortega, Daniel A. Braun:
A conversion between utility and information. CoRR abs/0911.5106 (2009) - 2008
- [i1]Pedro A. Ortega, Daniel A. Braun:
A Minimum Relative Entropy Principle for Learning and Acting. CoRR abs/0810.3605 (2008) - 2006
- [c1]Pedro A. Ortega, Cristián J. Figueroa, Gonzalo A. Ruz:
A Medical Claim Fraud/Abuse Detection System based on Data Mining: A Case Study in Chile. DMIN 2006: 224-231
Coauthor Index
aka: Daniel Alexander Braun
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